116 Interpretability Jobs - Page 2

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Azure Cloud and Python Developer for ML - Senior 1/2 EY GDS Consulting digital engineering, is seeking an experienced Azure Cloud and Python Developer for ML to join our Emerging Technologies team in DET, GDS. This role presents an exciting opportunity to contribute to innovative projects and be a key player in shaping our technological advancements. The opportunity We are seeking an experienced Azure Cloud and Python Developer with 6-8 years of hands-on experience in machine learning (ML) development. This role involves developing and deploying ML models on the Azure cloud platform, designing efficient data pipelines, and collaborating with data scientists and stakeholders to deliver technical solutions. Your Key Responsibilities Develop and deploy machine learning models on Azure cloud platform using Python programming language, ensuring scalability and efficiency. Design and implement scalable and efficient data pipelines for model training and inference, optimizing data processing workflows. Collaborate closely with data scientists and business stakeholders to understand requirements, translate them into technical solutions, and deliver high-quality ML solutions. Implement best practices for ML development, including version control using tools like Git, testing methodologies, and documentation to ensure reproducibility and maintainability. Design and optimize ML algorithms and data structures for performance and accuracy, leveraging Azure cloud services and Python libraries such as TensorFlow, PyTorch, or scikit-learn. Monitor and evaluate model performance, conduct experiments, and iterate on models to improve predictive accuracy and business outcomes. Work on feature engineering, data preprocessing, and feature selection techniques to enhance model performance and interpretability. Collaborate with DevOps teams to deploy ML models into production environments, ensuring seamless integration and continuous monitoring. Stay updated with the latest advancements in ML, Azure cloud services, and Python programming, and apply them to enhance ML capabilities and efficiency. Provide technical guidance and mentorship to junior developers and data scientists, fostering a culture of continuous learning and innovation. Skills And Attributes Soft Skills Bachelor's or master's degree in computer science, data science, or related field, with a strong foundation in ML algorithms, statistics, and programming concepts. Minimum 6-8 years of hands-on experience in developing and deploying ML models on Azure cloud platform using Python programming language. Expertise in designing and implementing scalable data pipelines for ML model training and inference, utilizing Azure Data Factory, Azure Databricks, or similar tools. Proficiency in Python programming language, including libraries such as TensorFlow, PyTorch, scikit-learn, pandas, and NumPy for ML model development and data manipulation. Strong understanding of ML model evaluation metrics, feature engineering techniques, and data preprocessing methods for structured and unstructured data. Experience with cloud-native technologies and services, including Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Functions, and Azure Storage. Familiarity with DevOps practices, CI/CD pipelines, and containerization tools like Docker for ML model deployment and automation. Excellent problem-solving skills, analytical thinking, and attention to detail, with the ability to troubleshoot and debug complex ML algorithms and systems. Effective communication skills, both verbal and written, with the ability to explain technical concepts to non-technical stakeholders and collaborate in cross-functional teams. Proactive and self-motivated attitude, with a passion for learning new technologies and staying updated with industry trends in ML, cloud computing, and software development. Strong organizational skills and the ability to manage multiple projects, prioritize tasks, and deliver results within project timelines and specifications. Business acumen and understanding of the impact of ML solutions on business operations and decision-making processes, with a focus on delivering value and driving business outcomes. Collaboration and teamwork skills, with the ability to work effectively in a global, diverse, and distributed team environment, fostering a culture of innovation and continuous improvement.. To qualify for the role, you must have A bachelor's or master's degree in computer science, data science, or related field, along with a minimum of 6-8 years of experience in ML development and Azure cloud platform expertise. Strong communication skills and consulting experience are highly desirable for this position. Ideally, you’ll also have Analytical ability to manage complex ML projects and prioritize tasks efficiently. Experience operating independently or with minimal supervision, demonstrating strong problem-solving skills. Familiarity with other cloud platforms and technologies such as AWS, Google Cloud Platform (GCP), or Kubernetes is a plus. What Working At EY Offers At EY, we’re dedicated to helping our clients, from start–ups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

Become our next FutureStarter Are you ready to make an impact? ZF is looking for talented individuals to join our team. As a FutureStarter, you’ll have the opportunity to shape the future of mobility. Join us and be part of something extraordinary! AI Research Scientist Country/Region: IN Location: Chennai, TN, IN, 600116 Req ID 79888 | GEC Chennai, India, ZF Commercial Vehicle Control Systems India Limited AI Research Scientist About the Team: ZF COE Team is effectively communicate complex technical concepts related to AI, ML, DL, and RL to both technical and non-technical audiences. This might involve presenting research findings at conferences or writing papers for academic journals. What you can look forward to as AI Research Scientist (m/f/d): Conduct cutting-edge research to identify and develop novel AI/ML methodologies, including Deep Learning (DL) and Reinforcement Learning (RL). Design and conduct experiments to test hypotheses, validate new approaches, and compare the effectiveness of different ML algorithms. Analyze data to uncover hidden patterns and relationships that can inform the development of new AI techniques. Stay at the forefront of the field by keeping abreast of the latest advancements in algorithms, tools, and theoretical frameworks. This might involve researching areas like interpretability of machine learning models or efficient training methods for deep neural networks. Prototype and explore the potential of advanced machine learning models, including deep learning architectures like convolutional neural networks (CNNs) or recurrent neural networks (RNNs). Contribute to the development of fundamental algorithms and frameworks that can be applied to various machine learning problems. This may involve improving existing algorithms or exploring entirely new approaches. Focus on theoretical aspects of model design, such as improving model efficiency, reducing bias, or achieving explainability in complex models. Document research methodologies, experimental procedures, and theoretical contributions for future reference and knowledge sharing within the research community. Contribute to the development of the research team's long-term research goals and strategies. Your profile as AI Research Scientist (m/f/d): Master's degree in Mathematics, Computer Science or other related technical fields. Phd is good to have. 8+ years of experience in research development, with a strong understanding of data structures and algorithms. 5+ years of experience building and deploying machine learning models in production. Proven experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. Experience with distributed computing systems and large-scale data processing & Excellent communication and collaboration skills. Contribution to invention disclosure process & A strong publication record in top machine learning conferences or journals. Why should you choose ZF Group in India? Innovative Environment: ZF is at the forefront of technological advancements, offering a dynamic and innovative work environment that encourages creativity and growth. Diverse and Inclusive Culture: ZF fosters a diverse and inclusive workplace where all employees are valued and respected, promoting a culture of collaboration and mutual support. Career Development: ZF is committed to the professional growth of its employees, offering extensive training programs, career development opportunities, and a clear path for advancement. Global Presence: As a part of a global leader in driveline and chassis technology, ZF provides opportunities to work on international projects and collaborate with teams worldwide. Sustainability Focus: ZF is dedicated to sustainability and environmental responsibility, actively working towards creating eco-friendly solutions and reducing its carbon footprint. Employee Well-being: ZF prioritizes the well-being of its employees, providing comprehensive health and wellness programs, flexible work arrangements, and a supportive work-life balance. Be part of our ZF team as AI Research Scientist and apply now! Contact Sowmya Nagarathinam What does DEI (Diversity, Equity, Inclusion) mean for ZF as a company? At ZF, we continuously strive to build and maintain a culture where inclusiveness is lived and diversity is valued. We actively seek ways to remove barriers so that all our employees can rise to their full potential. We aim to embed this vision in our legacy through how we operate and build our products as we shape the future of mobility. Find out how we work at ZF: Job Segment: Research Scientist, R&D, Computer Science, Scientist, Science, Research, Technology

About Us: Athena is India's largest institution in the "premium undergraduate study abroad" space. Founded 10 years ago by two Princeton graduates, Poshak Agrawal and Rahul Subramaniam, Athena is headquartered in Gurgaon, with offices in Mumbai and Bangalore, and caters to students from 26 countries. Athena’s vision is to help students become the best version of themselves. Athena’s transformative, holistic life coaching program embraces both depth and breadth, sciences and the humanities. Athena encourages students to deepen their theoretical knowledge and apply it to address practical issues confronting society, both locally and globally. Through our flagship program, our students have gotten into various, universities including Harvard University, Princeton University, Yale University, Stanford University, University of Cambridge, MIT, Brown, Cornell University, University of Pennsylvania, University of Chicago, among others. Learn more about Athena: https://www.athenaeducation.co.in/article.aspx Role Overview We are looking for an AI/ML Engineer who can mentor high-potential scholars in creating impactful technology projects. This role requires a blend of strong engineering expertise, the ability to distill complex topics into digestible concepts, and a deep passion for student-driven innovation. You’ll help scholars explore the frontiers of AI—from machine learning models to generative AI systems—while coaching them in best practices and applied engineering. Key Responsibilities: Guide scholars through the full AI/ML development cycle—from problem definition, data exploration, and model selection to evaluation and deployment. Teach and assist in building: Supervised and unsupervised machine learning models. Deep learning networks (CNNs, RNNs, Transformers). NLP tasks such as classification, summarization, and Q&A systems. Provide mentorship in Prompt Engineering: Craft optimized prompts for generative models like GPT-4 and Claude. Teach the principles of few-shot, zero-shot, and chain-of-thought prompting. Experiment with fine-tuning and embeddings in LLM applications. Support scholars with real-world datasets (e.g., Kaggle, open data repositories) and help integrate APIs, automation tools, or ML Ops workflows. Conduct internal training and code reviews, ensuring technical rigor in projects. Stay updated with the latest research, frameworks, and tools in the AI ecosystem. Technical Requirements: Proficiency in Python and ML libraries: scikit-learn, XGBoost, Pandas, NumPy. Experience with deep learning frameworks : TensorFlow, PyTorch, Keras. Strong command of machine learning theory , including: Bias-variance tradeoff, regularization, and model tuning. Cross-validation, hyperparameter optimization, and ensemble techniques. Solid understanding of data processing pipelines , data wrangling, and visualization (Matplotlib, Seaborn, Plotly). Advanced AI & NLP Experience with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on with LLM APIs : OpenAI (ChatGPT), Anthropic, Cohere, Hugging Face. Understanding of embedding-based retrieval , vector databases (e.g., Pinecone, FAISS), and Retrieval-Augmented Generation (RAG). Familiarity with AutoML tools , MLflow, Weights & Biases, and cloud AI platforms (AWS SageMaker, Google Vertex AI). Prompt Engineering & GenAI Proficiency in crafting effective prompts using: Instruction tuning Role-playing and system prompts Prompt chaining tools like LangChain or LlamaIndex Understanding of AI safety , bias mitigation, and interpretability. Required Qualifications: Bachelor’s degree from a Tier-1 Engineering College in Computer Science, Engineering, or a related field. 2-5 years of relevant experience in ML/AI roles. Portfolio of projects or publications in AI/ML (GitHub, blogs, competitions, etc.) Passion for education, mentoring , and working with high school scholars. Excellent communication skills, with the ability to convey complex concepts to a diverse audience. Preferred Qualifications: Prior experience in student mentorship, teaching, or edtech. Exposure to Arduino, Raspberry Pi, or IoT for integrated AI/ML projects. Strong storytelling and documentation abilities to help scholars write compelling project reports and research summaries. Show more Show less

Job description: What you can look forward to as Senior Data Scientist (m/f/d): · Conduct cutting-edge research to identify and develop novel AI/ML methodologies, including Deep Learning (DL) and Reinforcement Learning (RL). · Design and conduct experiments to test hypotheses, validate new approaches, and compare the effectiveness of different ML algorithms. · Analyze data to uncover hidden patterns and relationships that can inform the development of new AI techniques. · Stay at the forefront of the field by keeping abreast of the latest advancements in algorithms, tools, and theoretical frameworks. This might involve researching areas like interpretability of machine learning models or efficient training methods for deep neural networks. · Prototype and explore the potential of advanced machine learning models, including deep learning architectures like convolutional neural networks (CNNs) or recurrent neural networks (RNNs). · Contribute to the development of fundamental algorithms and frameworks that can be applied to various machine learning problems. This may involve improving existing algorithms or exploring entirely new approaches. · Focus on theoretical aspects of model design, such as improving model efficiency, reducing bias, or achieving explainability in complex models. · Document research methodologies, experimental procedures, and theoretical contributions for future reference and knowledge sharing within the research community. · Contribute to the development of the research team's long-term research goals and strategies. Your profile as Senior Data Scientist (m/f/d): · Master's degree in Mathematics, Computer Science or other related technical fields. Phd is good to have. · 8+ years of experience in research development, with a strong understanding of data structures and algorithms. · 5+ years of experience building and deploying machine learning models in production. · Proven experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. · Experience with distributed computing systems and large-scale data processing. · Excellent communication and collaboration skills. · Contribution to invention disclosure process. · A strong publication record in top machine learning conferences or journals. Show more Show less

Job description: What you can look forward to as AI Research Scientist (m/f/d): • Conduct cutting-edge research to identify and develop novel AI/ML methodologies, including Deep Learning (DL) and Reinforcement Learning (RL). • Design and conduct experiments to test hypotheses, validate new approaches, and compare the effectiveness of different ML algorithms. • Analyze data to uncover hidden patterns and relationships that can inform the development of new AI techniques. • Stay at the forefront of the field by keeping abreast of the latest advancements in algorithms, tools, and theoretical frameworks. This might involve researching areas like interpretability of machine learning models or efficient training methods for deep neural networks. • Prototype and explore the potential of advanced machine learning models, including deep learning architectures like convolutional neural networks (CNNs) or recurrent neural networks (RNNs). • Contribute to the development of fundamental algorithms and frameworks that can be applied to various machine learning problems. This may involve improving existing algorithms or exploring entirely new approaches. • Focus on theoretical aspects of model design, such as improving model efficiency, reducing bias, or achieving explainability in complex models. • Document research methodologies, experimental procedures, and theoretical contributions for future reference and knowledge sharing within the research community. • Contribute to the development of the research team's long-term research goals and strategies. Your profile as AI Research Scientist (m/f/d): • Master's degree in Mathematics, Computer Science or other related technical fields. Phd is good to have. • 8+ years of experience in research development, with a strong understanding of data structures and algorithms. • 5+ years of experience building and deploying machine learning models in production. • Proven experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. • Experience with distributed computing systems and large-scale data processing & Excellent communication and collaboration skills. • Contribution to invention disclosure process & A strong publication record in top machine learning conferences or journals. Profile description: What you can look forward to as AI Research Scientist (m/f/d): • Conduct cutting-edge research to identify and develop novel AI/ML methodologies, including Deep Learning (DL) and Reinforcement Learning (RL). • Design and conduct experiments to test hypotheses, validate new approaches, and compare the effectiveness of different ML algorithms. • Analyze data to uncover hidden patterns and relationships that can inform the development of new AI techniques. • Stay at the forefront of the field by keeping abreast of the latest advancements in algorithms, tools, and theoretical frameworks. This might involve researching areas like interpretability of machine learning models or efficient training methods for deep neural networks. • Prototype and explore the potential of advanced machine learning models, including deep learning architectures like convolutional neural networks (CNNs) or recurrent neural networks (RNNs). • Contribute to the development of fundamental algorithms and frameworks that can be applied to various machine learning problems. This may involve improving existing algorithms or exploring entirely new approaches. • Focus on theoretical aspects of model design, such as improving model efficiency, reducing bias, or achieving explainability in complex models. • Document research methodologies, experimental procedures, and theoretical contributions for future reference and knowledge sharing within the research community. • Contribute to the development of the research team's long-term research goals and strategies. Your profile as AI Research Scientist (m/f/d): • Master's degree in Mathematics, Computer Science or other related technical fields. Phd is good to have. • 8+ years of experience in research development, with a strong understanding of data structures and algorithms. • 5+ years of experience building and deploying machine learning models in production. • Proven experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn. • Experience with distributed computing systems and large-scale data processing & Excellent communication and collaboration skills. • Contribution to invention disclosure process & A strong publication record in top machine learning conferences or journals. Show more Show less

We are seeking a seasoned and visionary Lead AI Engineer to drive the design, development, and delivery of high-impact AI/ML solutions. As a technical leader, you will guide a team of AI developers in executing large-scale AI/ML projects, mentor them to build expertise, and foster a culture of innovation and excellence. You will collaborate with sales teams during pre-sales calls to articulate technical solutions and work closely with leadership to translate strategic vision into actionable, production-ready AI systems. Responsibilities Architect and lead the end-to-end development of impactful AI/ML models and systems, ensuring scalability, reliability, and performance. Provide hands-on technical guidance to a team of AI/ML engineers, fostering skill development and promoting best practices in coding, model design, and experimentation. Collaborate with cross-functional teams, including data scientists, product managers, and software developers, to define AI product strategies and roadmaps. Partner with the sales team during pre-sales calls to understand client needs, propose AI-driven solutions, and communicate technical feasibility. Translate leadership’s strategic vision into technical requirements and executable project plans. Design and implement scalable MLOps infrastructure for data ingestion, model training, evaluation, deployment, and monitoring. Lead research and experimentation in advanced AI domains such as NLP, computer vision, large language models (LLMs), or generative AI, tailoring solutions to business needs. Evaluate and integrate open-source or commercial AI frameworks/tools to accelerate development and ensure robust solutions. Monitor and optimize deployed models for performance, fairness, interpretability, and cost-efficiency, driving continuous improvement. Mentor and nurture new talent, building a high-performing AI team capable of delivering complex projects over time. Qualifications Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, or a related field. 5+ years of hands-on experience in machine learning or deep learning, with a proven track record of delivering large-scale AI/ML projects to production. Demonstrated ability to lead and mentor early-career engineers, fostering technical growth and team collaboration. Strong proficiency in Python and ML frameworks/libraries (e.g., TensorFlow, PyTorch, HuggingFace, Scikit-learn). Extensive experience deploying AI models in production environments using tools like AWS SageMaker, Google Vertex AI, Docker, Kubernetes, or similar. Solid understanding of data pipelines, APIs, MLOps practices, and software engineering principles. Experience collaborating with non-technical stakeholders (e.g., sales, leadership) to align technical solutions with business objectives. Familiarity with advanced AI domains such as NLP, computer vision, LLMs, or generative AI is a plus. Excellent communication skills to articulate complex technical concepts to diverse audiences, including clients and executives. Strong problem-solving skills, with a proactive approach to driving innovation and overcoming challenges. Show more Show less

Project Role : Security Delivery Lead Project Role Description : Leads the implementation and delivery of Security Services projects, leveraging our global delivery capability (method, tools, training, assets). Must have skills : Product Security Good to have skills : NA Minimum 12 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: AI Security Architect – Enterprise AI Strategy, Scalable ML Platforms, and Secure AI Design We are looking for a seasoned and visionary AI Architect with 12+ years of experience in designing, securing, and leading scalable, responsible AI systems. This role blends AI solution architecture with security architecture and is ideal for professionals who bring together deep technical knowledge, strategic thinking, and a passion for trustworthy, ethical innovation. As an AI Architect, you will define the enterprise AI and security architecture, embed secure-by-design practices across AI platforms, and ensure alignment with privacy, compliance, and ethical standards across the entire ML lifecycle Roles & Responsibilities: Own the architectural vision for enterprise-wide AI and ML platforms, ensuring scalability, resilience, security, and regulatory compliance. Develop and maintain architectural blueprints for secure and responsible AI, covering areas such as bias mitigation, explainability, threat modeling, and data protection. Define and implement AI security architecture practices, including secure access to models, datasets, APIs, and ML pipelines. Collaborate with MLOps, engineering, DevSecOps, and cloud security teams to develop standardized, reusable, and secured AI infrastructure components. Ensure AI systems comply with global regulations and standards (e.g., GDPR, ISO 42001, NIST AI RMF, and ISO/IEC 27001). Evaluate and introduce tools and frameworks that support privacy-preserving AI, adversarial robustness, model security, and interpretability. Job Title - Industry X + Manager + IMU Management Level : 07 – Manager Location: New Delhi Must have skills: In-depth understanding of Industry X concepts, technologies (e.g., Industrial IoT, Predictive Maintenance, Digital Twins), and their application in discrete manufacturing operations. Strong understanding of lean manufacturing principles and their integration with Industry X solutions. Good to have skills: Experience working with Manufacturing Execution Systems (MES) and other relevant industry-specific software is a plus. Job Summary: As an Industry X expert, you will be responsible to drive client value creation through participating in Industry X (Digital Transformation) related projected deliveries as well as support in end-to-end sales lifecycle (deal origination to sales) Roles & Responsibilities: Drive client value creation through participating in Industry X(Digital Transformation) related projected deliveries as well as support in end-to-end sales lifecycle (deal origination to sales) Conduct in-depth assessments of client manufacturing operations to identify areas ripe for Industry X interventions Strong understanding of digital/AI use-cases and impact in manufacturing operations Analyze client needs and translate them into actionable roadmaps incorporating relevant Industry X technologies such as IoT, Big Data, Cloud, AI, and Machine Learning. Develop and present compelling business cases highlighting the potential return on investment (ROI) associated with Industry X initiatives. Manage and lead client engagements, ensuring successful project execution within budget and timelines. Partner with internal and external stakeholders, including technology vendors and system integrators, to deliver seamless project implementation. Stay abreast of the latest Industry X trends and technologies, continuously expanding your knowledge base to provide clients with cutting-edge insights. Establish self as a trusted advisor with the client C-suite through an in-depth understanding of the client as well as industry Build networks at Accenture to be able to bring the best of Accenture to the client Professional & Technical Skills: Minimum 10+ years of experience in management consulting, with a strong track record in Resources industries such as: Automotive (Auto parts, Cars, Trucks) Electronics & Semiconductors (Integrated circuits, Printed circuit boards) Machinery & Equipment (Industrial machinery, Construction equipment) Proven experience in successfully leading and managing complex client engagements within the discrete manufacturing domain. In-depth understanding of Industry X concepts, technologies (e.g., Industrial IoT, Predictive Maintenance, Digital Twins), and their application in discrete manufacturing operations. Strong understanding of lean manufacturing principles and their integration with Industry X solutions. Experience working with Manufacturing Execution Systems (MES) and other relevant industry-specific software is a plus. Additional Information: The ideal candidate will possess a strong background in using data and technologies such as AR/VR, cloud, AI, 5G, robotics and digital twins, work with market leaders to build resilient and agile businesses that adapt engineering, infrastructure & capital projects, manufacturing operations in the face of change. This position is based at our New Delhi office. About Our Company | Accenture Experience: Minimum 10 year(s) of experience is required Educational Qualification: Bachelor's degree in Engineering, Business Administration, or a related field, with a focus in industrial engineering, manufacturing engineering, or a similar discipline. Show more Show less

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Years of Experience: Candidates with 15+ years of hands on experience Required Skills Must Have: Solid knowledge and experience of supervised, unsupervised machine learning algorithms. For e.g (but not limited to): linear regressions, bayesian regressions, multi objective optimization techniques, classifiers, cluster analysis, dimension reduction etc. Understanding of technicality used for retail analytics across loyalty, customer analytics, assortment, promotion and marketing Good knowledge of statistics For e.g: statistical tests & distributions Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib) Advanced level programming in SQL and Python/Pyspark to guide teams Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc. Nice To Have Working knowledge of containerization ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. Airflow) Experience with model explainability and interpretability techniques Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product Ability to think through complex user scenarios and design simple yet effective user interactions Good Communication and presentation skills Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA Show more Show less

PwC is one of the most prestigious professional services firm in the world, serving as the auditor to nearly half of the world’s largest banks. PwC US Risk and Regulatory (R&R) comprises of a highly experienced team of risk management specialists supporting global financial institutions in their risk management initiatives. R&R has significant exposure to, and driver of, industry leading practices and has deep knowledge of regulatory expectations. R&R professional’s experience covers all financial model types, including those used to manage credit risk, market risk, operational risk and compliance risk—as well as those used for financial reporting, valuations and economic capital estimation. Risk Analytics Center of Excellence (CoE) is the India extension of R&R practice and provides key risk analytics services to global banks, investment firms, and asset management entities. It comprises of risk analytics professionals with stellar quantitative pedigree from premier institutions, industry certifications in CFA, FRM, PRM etc. and proven professional credentials in risk modeling and analytics at reputed financial institutions and consulting firms. As an integral part of PwC US R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cutting-edge innovation using data science, Artificial Intelligence, Machine Learning and Deep Learning. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred Show more Show less

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred Show more Show less

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Apply a learning mindset and take ownership for your own development. Appreciate diverse perspectives, needs, and feelings of others. Adopt habits to sustain high performance and develop your potential. Actively listen, ask questions to check understanding, and clearly express ideas. Seek, reflect, act on, and give feedback. Gather information from a range of sources to analyse facts and discern patterns. Commit to understanding how the business works and building commercial awareness. Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred Show more Show less

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation. Years of Experience: Candidates with 15+ years of hands on experience Required Skills Must Have: Solid knowledge and experience of supervised, unsupervised machine learning algorithms. For e.g (but not limited to): linear regressions, bayesian regressions, multi objective optimization techniques, classifiers, cluster analysis, dimension reduction etc. Understanding of technicality used for retail analytics across loyalty, customer analytics, assortment, promotion and marketing Good knowledge of statistics For e.g: statistical tests & distributions Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow,, Pytorch, MLlib) Advanced level programming in SQL and Python/Pyspark to guide teams Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc. Nice To Have Working knowledge of containerization ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. Airflow) Experience with model explainability and interpretability techniques Multi-task and manage multiple deadlines. Responsible for incorporating client/user feedback into the Product Ability to think through complex user scenarios and design simple yet effective user interactions Good Communication and presentation skills Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech / MBA Show more Show less

Job Information Company Accumn Date Opened 06/06/2025 Job Type Full time Industry Financial Services City Ahmadabad City State/Province Gujarat Country India Zip/Postal Code 380001 About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. Job Description About the company: Accumn - a Yubi company, is India’s most advanced AI-first credit decisioning platform, integrating machine learning (ML) and generative artificial intelligence (GenAI) to empower credit managers with precise, data-driven tools for fair and transparent lending decisions. Formed through the strategic consolidation of Corpository and FinFort, Accumn offers a comprehensive suite of solutions to support the entire credit lifecycle—from lead generation and risk management to post- disbursement monitoring. With over 1 lakh active banking and credit users, Accumn has achieved a 66% reduction in credit processing time and boasts an 85% success rate in predicting defaults. The platform has over 5 lakh entities under credit monitoring. The company has been recognized for “Best Use of AI & ML Models for Credit Default Prediction” by Banking Frontiers and “Best Use of AI in Risk Evaluation” by Dun & Bradstreet. Visit www.hello.accumn.ai and www.go-yubi.com to learn more. About the Role: We are looking for an experienced Analyst to spearhead the Analytics initiatives comprising of cutting-edge credit risk assessment models, Unstructured document reading solutions, Data Analysis and more for our banking, NBFC, and fintech customers. In this pivotal role, you will build credit underwriting and risk management strategies, champion innovation in AI/ML-powered customer journey mapping, and drive the development of transformative product solutions for our lending partners. You will leverage your expertise to deliver industry-leading, technology-enabled credit underwriting and risk assessment solutions—empowering lenders to make precise, data- driven lending decisions and mitigate financial risks effectively. Education: CA/CFA/MBA(Finance)  Credit Underwriting Expertise: Provide strategic leadership in credit underwriting and risk management practices for banks, NBFCs, and fintech companies. Implement industry best practices ensuring optimized risk assessment and compliance.  AI/ML Customer Journey Mapping: Build real-time AI/ML models for personalized customer journey mapping, leveraging transaction history, 1:1 engagement, demographics, language preferences, and behavior analytics to enhance credit decisioning.  Scorecard Innovation: Pioneer the design and implementation of cutting-edge scorecards and risk models, harnessing AI and machine learning for highly accurate and explainable risk predictions, coverages of financial performance and compliance indicators.  Exceeding Customer Expectations: Engage proactively with clients, deeply understanding their business requirements. Ensure all analytical models and scorecards not only meet but exceed customer expectations, delivering reliable, actionable insights in a timely manner. Collaborate with sales, products and engineering teams to ensure that customers’ expectations and experiences are met and delivered.  Computer Vision & NLP Applications: Lead initiatives applying ML/AI, computer vision, and natural language processing to extract data from unstructured documents (bank statements, financial statements, notes) to add new dimensions to credit analysis.  Generative AI & Advanced Risk Assessment: Spearhead the training and deployment of generative AI models, yielding sharper risk insights and enabling constructive, forward-looking data analysis.  Product Development Leadership: Collaborate with engineering and product teams to drive the integration of AI/ML into next-generation financial products and systems, ensuring solutions are tailored for the unique needs of the banking and lending industries.  Data Transformation & Reporting: Transform publicly available and internal data into actionable reports, alerts, triggers, and scorecards. Lead the development of automation tools and systems that streamline analysis and reduce manual workloads.  Business Requirements & Leadership: Drive complex, cross-functional requirements gathering, documentation (including PRDs), and project delivery. Engage in maintaining and prioritising Product backlog to accommodate business needs. Build and mentor high-performing teams, establish best-in-class processes, and foster a culture of operational excellence.  Communication & multi-tasking: Articulate complex concepts to diverse stakeholders. Expertly manage competing priorities and deliver quality results within tight deadlines, thriving in fast-paced, dynamic environments. Requirements  CFA Charter holder or equivalent advanced degree with relevant experience in financial analysis.  8+ years of experience in developing credit risk modelling, financial analysis, or related roles within banking, NBFC, or fintech organizations.  Prior experience in developing credit underwriting and risk assessment score cards/models using computer vision (CV), natural language processing (NLP), and generative AI will be preferred.  Deep knowledge of scorecard development, statistical techniques, and interpretability/significance of model outputs.  Proven hands-on expertise in AI/ML model development for credit underwriting, especially using Python, R, or similar platforms.  Track record of successful product development from prototype through launch stage, especially for credit and risk management solutions.  Strong project management, team leadership, and stakeholder engagement skills.  Excellent written and verbal communication skills.  Excellent Data analysis, data visualisation skills.

We are seeking a highly skilled and motivated Lead DS/ML engineer to join our team. The role is critical to the development of a cutting-edge reporting platform designed to measure and optimize online marketing campaigns. We are seeking a highly skilled Data Scientist / ML Engineer with a strong foundation in data engineering (ELT, data pipelines) and advanced machine learning to develop and deploy sophisticated models. The role focuses on building scalable data pipelines, developing ML models, and deploying solutions in production to support a cutting-edge reporting, insights, and recommendations platform for measuring and optimizing online marketing campaigns. The ideal candidate should be comfortable working across data engineering, ML model lifecycle, and cloud-native technologies. Job Description: Key Responsibilities: Data Engineering & Pipeline Development Design, build, and maintain scalable ELT pipelines for ingesting, transforming, and processing large-scale marketing campaign data. Ensure high data quality, integrity, and governance using orchestration tools like Apache Airflow, Google Cloud Composer, or Prefect. Optimize data storage, retrieval, and processing using BigQuery, Dataflow, and Spark for both batch and real-time workloads. Implement data modeling and feature engineering for ML use cases. Machine Learning Model Development & Validation Develop and validate predictive and prescriptive ML models to enhance marketing campaign measurement and optimization. Experiment with different algorithms (regression, classification, clustering, reinforcement learning) to drive insights and recommendations. Leverage NLP, time-series forecasting, and causal inference models to improve campaign attribution and performance analysis. Optimize models for scalability, efficiency, and interpretability. MLOps & Model Deployment Deploy and monitor ML models in production using tools such as Vertex AI, MLflow, Kubeflow, or TensorFlow Serving. Implement CI/CD pipelines for ML models, ensuring seamless updates and retraining. Develop real-time inference solutions and integrate ML models into BI dashboards and reporting platforms. Cloud & Infrastructure Optimization Design cloud-native data processing solutions on Google Cloud Platform (GCP), leveraging services such as BigQuery, Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow. Work on containerized deployment (Docker, Kubernetes) for scalable model inference. Implement cost-efficient, serverless data solutions where applicable. Business Impact & Cross-functional Collaboration Work closely with data analysts, marketing teams, and software engineers to align ML and data solutions with business objectives. Translate complex model insights into actionable business recommendations. Present findings and performance metrics to both technical and non-technical stakeholders. Qualifications & Skills: Educational Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. Certifications in Google Cloud (Professional Data Engineer, ML Engineer) is a plus. Must-Have Skills: Experience: 5-10 years with the mentioned skillset & relevant hands-on experience Data Engineering: Experience with ETL/ELT pipelines, data ingestion, transformation, and orchestration (Airflow, Dataflow, Composer). ML Model Development: Strong grasp of statistical modeling, supervised/unsupervised learning, time-series forecasting, and NLP. Programming: Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL for large-scale data processing. Cloud & Infrastructure: Expertise in GCP (BigQuery, Vertex AI, Dataflow, Pub/Sub, Cloud Storage) or equivalent cloud platforms. MLOps & Deployment: Hands-on experience with CI/CD pipelines, model monitoring, and version control (MLflow, Kubeflow, Vertex AI, or similar tools). Data Warehousing & Real-time Processing: Strong knowledge of modern data platforms for batch and streaming data processing. Nice-to-Have Skills: Experience with Graph ML, reinforcement learning, or causal inference modeling. Working knowledge of BI tools (Looker, Tableau, Power BI) for integrating ML insights into dashboards. Familiarity with marketing analytics, attribution modeling, and A/B testing methodologies. Experience with distributed computing frameworks (Spark, Dask, Ray). Location: Bengaluru Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

The HiLabs Story HiLabs is a leading provider of AI-powered solutions to clean dirty data, unlocking its hidden potential for healthcare transformation. HiLabs is committed to transforming the healthcare industry through innovation, collaboration, and a relentless focus on improving patient outcomes. HiLabs Team Multidisciplinary industry leaders Healthcare domain experts AI/ML and data science experts Professionals hailing from the worlds best universities, business schools, and engineering institutes including Harvard, Yale, Carnegie Mellon, Duke, Georgia Tech, Indian Institute of Management (IIM), and Indian Institute of Technology (IIT). As a Data Scientist at HiLabs, you will partner closely with a team of stake holders, product managers, and data engineers to solve real problems in healthcare domain. HiLabs is looking for great problem solvers who can tap into the potential of data and deliver scalable and robust data products. Our potential member would work on developing and implementing machine learning algorithms for various HiLabs Products and Solutions. Responsibilities Leveraging AI/ML techniques and solutions to identify and mathematically interpret complex healthcare problems. Deploy and optimize machine learning solutions on massive datasets using big data technologies. Develop and prototype AI algorithms and software tools. Implement enhancements to existing algorithmic/deep learning solutions. Conduct quantitative data analysis using a variety of datasets. Increase the efficiency and improve the quality of solutions offered. Understand business use cases and pull the necessary data from various sources to provide key insights to stakeholders. Build and deploy additional functionalities as per client requirements. Leverage recent advances in machine learning technologies and oversee the team’s training. For Lead/Sr. Data Scientists-Lead a team of Data Scientists, developers as well as clinicians to strategize, design and evaluate AI based solutions to healthcare problems. Desired Profile:. Bachelor’s Degree/Master’s Degree in Computer Science, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering or related fields from tier 1 college. Hands-on Software Development Skills (Scala-Preferred). Experience or educational courses/projects in Machine Learning, and/or Text Mining Algorithms. Knowledge of statistical techniques, linear algebra, numerical optimization. Knowledge of ML theory such as bias variance tradeoff, regularization, loss functions and experienced in A/B testing. Know all the general best practices of Machine Learning. Ability to work closely with Domain experts to develop tools/algorithms needed to answer research questions in their studies. Excellent Communication Skills (with the ability to explain developed tools and ML algorithms to a non-technical audience). Ability to formulate operational problems in healthcare domain as technical problems that allows for reuse of leading research in the area. Proven ability to work independently to learn new technologies, techniques, processes, languages, platforms, systems. Strong analytical, inferential, critical thinking, and creative problem-solving skills. Self-starter with ability to work both independently and with a team. Preferred Qualifications Experience with Deep Learning Frameworks such as Keras, Tensorflow, PyTorch,Mxnet etc. Experience with interpretability of deep learning models. Big Data Skills (Hadoop, Spark, recent deep learning platforms). Experience with text mining tools and techniques including in areas of summarization, search (e.g. ELK Stack), entity extraction, training set generation (e.g. Snorkel) and anomaly detection. Expert software development skills including developing and maintaining production quality code HiLabs Total Rewards Competitive Salary, Accelerated Incentive Policies, H1B sponsorship, Comprehensive benefits package that includes ESOPs, financial contribution for your ongoing professional and personal development, medical coverage for you and your loved ones, 401k, PTOs & a collaborative working environment, Smart mentorship, and highly qualified multidisciplinary, incredibly talented professionals from highly renowned and accredited medical schools, business schools, and engineering institutes. CCPA disclosure notice - https://www.hilabs.com/privacy Show more Show less

About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. About the company: Accumn - a Yubi company, is India’s most advanced AI-first credit decisioning platform, integrating machine learning (ML) and generative artificial intelligence (GenAI) to empower credit managers with precise, data-driven tools for fair and transparent lending decisions. Formed through the strategic consolidation of Corpository and FinFort, Accumn offers a comprehensive suite of solutions to support the entire credit lifecycle—from lead generation and risk management to post- disbursement monitoring. With over 1 lakh active banking and credit users, Accumn has achieved a 66% reduction in credit processing time and boasts an 85% success rate in predicting defaults. The platform has over 5 lakh entities under credit monitoring. The company has been recognized for “Best Use of AI & ML Models for Credit Default Prediction” by Banking Frontiers and “Best Use of AI in Risk Evaluation” by Dun & Bradstreet. Visit www.hello.accumn.ai and www.go-yubi.com to learn more. About the Role: We are looking for an experienced Analyst to spearhead the Analytics initiatives comprising of cutting-edge credit risk assessment models, Unstructured document reading solutions, Data Analysis and more for our banking, NBFC, and fintech customers. In this pivotal role, you will build credit underwriting and risk management strategies, champion innovation in AI/ML-powered customer journey mapping, and drive the development of transformative product solutions for our lending partners. You will leverage your expertise to deliver industry-leading, technology-enabled credit underwriting and risk assessment solutions—empowering lenders to make precise, data- driven lending decisions and mitigate financial risks effectively. Education: CA/CFA/MBA(Finance)  Credit Underwriting Expertise: Provide strategic leadership in credit underwriting and risk management practices for banks, NBFCs, and fintech companies. Implement industry best practices ensuring optimized risk assessment and compliance.  AI/ML Customer Journey Mapping: Build real-time AI/ML models for personalized customer journey mapping, leveraging transaction history, 1:1 engagement, demographics, language preferences, and behavior analytics to enhance credit decisioning.  Scorecard Innovation: Pioneer the design and implementation of cutting-edge scorecards and risk models, harnessing AI and machine learning for highly accurate and explainable risk predictions, coverages of financial performance and compliance indicators.  Exceeding Customer Expectations: Engage proactively with clients, deeply understanding their business requirements. Ensure all analytical models and scorecards not only meet but exceed customer expectations, delivering reliable, actionable insights in a timely manner. Collaborate with sales, products and engineering teams to ensure that customers’ expectations and experiences are met and delivered.  Computer Vision & NLP Applications: Lead initiatives applying ML/AI, computer vision, and natural language processing to extract data from unstructured documents (bank statements, financial statements, notes) to add new dimensions to credit analysis.  Generative AI & Advanced Risk Assessment: Spearhead the training and deployment of generative AI models, yielding sharper risk insights and enabling constructive, forward-looking data analysis.  Product Development Leadership: Collaborate with engineering and product teams to drive the integration of AI/ML into next-generation financial products and systems, ensuring solutions are tailored for the unique needs of the banking and lending industries.  Data Transformation & Reporting: Transform publicly available and internal data into actionable reports, alerts, triggers, and scorecards. Lead the development of automation tools and systems that streamline analysis and reduce manual workloads.  Business Requirements & Leadership: Drive complex, cross-functional requirements gathering, documentation (including PRDs), and project delivery. Engage in maintaining and prioritising Product backlog to accommodate business needs. Build and mentor high-performing teams, establish best-in-class processes, and foster a culture of operational excellence.  Communication & multi-tasking: Articulate complex concepts to diverse stakeholders. Expertly manage competing priorities and deliver quality results within tight deadlines, thriving in fast-paced, dynamic environments. Requirements  CFA Charter holder or equivalent advanced degree with relevant experience in financial analysis.  8+ years of experience in developing credit risk modelling, financial analysis, or related roles within banking, NBFC, or fintech organizations.  Prior experience in developing credit underwriting and risk assessment score cards/models using computer vision (CV), natural language processing (NLP), and generative AI will be preferred.  Deep knowledge of scorecard development, statistical techniques, and interpretability/significance of model outputs.  Proven hands-on expertise in AI/ML model development for credit underwriting, especially using Python, R, or similar platforms.  Track record of successful product development from prototype through launch stage, especially for credit and risk management solutions.  Strong project management, team leadership, and stakeholder engagement skills.  Excellent written and verbal communication skills.  Excellent Data analysis, data visualisation skills. 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This role is for one of our clients Industry: Technology, Information and Media Seniority level: Mid-Senior level About the Role We’re seeking an experienced and forward-thinking Lead AI Engineer to head the development of cutting-edge AI applications leveraging large language models (LLMs) and generative AI techniques. In this high-impact role, you will guide the architecture, deployment, and optimization of AI systems that power real-world, intelligent applications. You’ll be at the intersection of research and engineering, leading a team of top-tier AI engineers while shaping the future of AI capabilities within the organization. What You’ll Do Architect AI Solutions Design and lead the development of end-to-end AI systems that leverage LLMs, retrieval-augmented generation (RAG), and autonomous agent frameworks. Model Integration and Optimization Work hands-on with both open-source (Llama, Mistral, Falcon, etc.) and proprietary models (GPT-4, Claude, Gemini), fine-tuning them for specialized applications using proprietary data. Agentic Systems & RAG Build intelligent agents capable of reasoning, planning, and performing multi-step tasks using agentic architectures and RAG pipelines with vector databases like FAISS or Weaviate. Production-Grade Engineering Oversee scalable deployment, versioning, and monitoring of AI models in production using modern MLOps practices and cloud-native platforms (AWS, GCP, Azure). Cross-functional Collaboration Partner with data scientists, product managers, and software engineers to transform complex problems into elegant AI-driven products. AI Team Leadership Mentor a team of engineers, drive technical direction, and manage project priorities, sprint planning, and roadmap execution. Innovation & Research Stay ahead of the curve by tracking advancements in the AI/LLM space. Promote a culture of experimentation, rapid prototyping, and responsible AI. Ethics & Evaluation Implement best practices for model interpretability, bias mitigation, and responsible deployment of AI systems. Must-Have Qualifications Experience 5+ years of hands-on experience in AI/ML engineering with a primary focus on NLP and LLMs. Proven experience in designing and deploying production-grade AI systems. Technical Skills Strong command of Python and frameworks like PyTorch , TensorFlow , LangChain , and LlamaIndex . Solid knowledge of transformer architectures , embeddings, fine-tuning techniques, and tokenization. Experience integrating with vector databases (FAISS, Pinecone, Weaviate). Proficiency in designing APIs and working with distributed systems . Familiarity with MLOps , containerization (Docker), and orchestration tools (Kubernetes). Leadership Experience managing engineering teams and projects, with a track record of shipping successful AI solutions. Cloud & Deployment Deep experience with deploying AI systems on AWS , GCP , or Azure , and optimizing workloads for cost and performance. Nice-to-Have Experience working with multi-modal AI models (text, image, video, audio). Knowledge of RLHF (Reinforcement Learning from Human Feedback) methodologies. Contributions to open-source AI projects or peer-reviewed research. Prior experience at a startup or AI research lab .

Job Description: Data Scientist (Intern) Position Overview: As a Data Scientist, you will be responsible for analyzing and interpreting complex datasets to provide valuable insights and solve challenging business problems. You will work closely with cross-functional teams to gather data, build predictive models, develop algorithms, and deliver data-driven solutions. This position is ideal for a fresher who possesses strong analytical skills, programming expertise, and a passion for working with data. Key Responsibilities: Data Collection and Preprocessing: Collect, clean, and preprocess large volumes of structured and unstructured data from various sources. Conduct data quality assessments and implement data cleaning techniques to ensure accuracy and reliability. Exploratory Data Analysis (EDA): Perform exploratory data analysis to understand the characteristics of the data and identify patterns, trends, and outliers. Utilize statistical techniques and visualizations to gain insights from the data. Statistical Modeling and Machine Learning: Develop predictive models and algorithms using statistical techniques and machine learning algorithms. Apply regression analysis, classification, clustering, time series analysis, and other relevant methods to solve business problems. Evaluate model performance, fine-tune parameters, and optimize models for better accuracy. Feature Engineering: Identify and engineer relevant features from raw data to enhance model performance. Conduct feature selection techniques to improve model interpretability and efficiency. Model Deployment and Evaluation: Collaborate with software engineers to deploy models into production systems. Monitor model performance, diagnose issues, and implement improvements as needed. Data Visualization and Reporting: Communicate findings and insights effectively through clear and concise data visualizations, reports, and presentations. Present complex data-driven concepts to non-technical stakeholders in a way that is easy to understand. Continuous Learning and Research: Stay up-to-date with the latest advancements in data science, machine learning, and related fields. Conduct research and experimentation to explore new methodologies and approaches. Show more Show less

Role Overview We are seeking a QA Manager with strong experience in test automation and a passion for AI . You will lead a team of QA engineers and work closely with cross-functional stakeholders to build robust testing frameworks, introduce intelligent automation, and ensure end-to-end product quality. You’ll also play a key role in shaping how AI can be used to improve QA efficiency and software reliability. Key Responsibilities Own the QA strategy, test planning, and execution for web, mobile, and API-based applications. Lead, mentor, and grow a team of QA engineers and SDETs. Design and implement automation frameworks using modern tools (e.g., Selenium, Cypress, Playwright, Appium). Evaluate and integrate AI-driven QA tools (e.g., Testim, Mabl, Functionize, Diffblue, ChatGPT-based test case generation). Drive continuous integration and delivery (CI/CD) of automated tests across environments. Establish test data strategies using synthetic data generation and AI-based test data tools. Collaborate with product managers, developers, and DevOps teams to define acceptance criteria and promote shift-left testing. Monitor quality metrics and use analytics to improve test coverage, defect detection, and release velocity. Stay abreast of emerging QA trends, especially in AI/ML validation, generative AI testing, and model interpretability QA. Required Skills & Qualifications 8+ years of experience in Quality Assurance, with at least 3 years in a managerial or leadership role. Proven track record in building and scaling test automation for complex systems. Experience with at least one programming language (Python, Java, JavaScript preferred). Hands-on experience with AI-powered QA tools or building AI/ML pipelines with embedded QA. Solid understanding of AI/ML concepts such as model training, inference, data drift, and validation. Strong knowledge of testing practices: unit, integration, functional, performance, regression, security. Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab, etc.). Familiarity with cloud platforms (AWS, Azure, or GCP) and containerized environments (Docker, Kubernetes). Excellent leadership, communication, and stakeholder management skills. Nice to Have Exposure to MLOps or AI model lifecycle QA. Experience in regulatory or enterprise-level compliance QA (e.g., SOC2, GDPR). Contributions to open-source QA projects or AI QA communities. Show more Show less

Job Information Company Accumn Date Opened 06/06/2025 Job Type Full time Industry Financial Services City Ahmadabad City State/Province Gujarat Country India Zip/Postal Code 380001 About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. Job Description About the company: Accumn - a Yubi company, is India’s most advanced AI-first credit decisioning platform, integrating machine learning (ML) and generative artificial intelligence (GenAI) to empower credit managers with precise, data-driven tools for fair and transparent lending decisions. Formed through the strategic consolidation of Corpository and FinFort, Accumn offers a comprehensive suite of solutions to support the entire credit lifecycle—from lead generation and risk management to post- disbursement monitoring. With over 1 lakh active banking and credit users, Accumn has achieved a 66% reduction in credit processing time and boasts an 85% success rate in predicting defaults. The platform has over 5 lakh entities under credit monitoring. The company has been recognized for “Best Use of AI & ML Models for Credit Default Prediction” by Banking Frontiers and “Best Use of AI in Risk Evaluation” by Dun & Bradstreet. Visit www.hello.accumn.ai and www.go-yubi.com to learn more. About the Role: We are looking for an experienced Analyst to spearhead the Analytics initiatives comprising of cutting-edge credit risk assessment models, Unstructured document reading solutions, Data Analysis and more for our banking, NBFC, and fintech customers. In this pivotal role, you will build credit underwriting and risk management strategies, champion innovation in AI/ML-powered customer journey mapping, and drive the development of transformative product solutions for our lending partners. You will leverage your expertise to deliver industry-leading, technology-enabled credit underwriting and risk assessment solutions—empowering lenders to make precise, data- driven lending decisions and mitigate financial risks effectively. Education: CA/CFA/MBA(Finance)  Credit Underwriting Expertise: Provide strategic leadership in credit underwriting and risk management practices for banks, NBFCs, and fintech companies. Implement industry best practices ensuring optimized risk assessment and compliance.  AI/ML Customer Journey Mapping: Build real-time AI/ML models for personalized customer journey mapping, leveraging transaction history, 1:1 engagement, demographics, language preferences, and behavior analytics to enhance credit decisioning.  Scorecard Innovation: Pioneer the design and implementation of cutting-edge scorecards and risk models, harnessing AI and machine learning for highly accurate and explainable risk predictions, coverages of financial performance and compliance indicators.  Exceeding Customer Expectations: Engage proactively with clients, deeply understanding their business requirements. Ensure all analytical models and scorecards not only meet but exceed customer expectations, delivering reliable, actionable insights in a timely manner. Collaborate with sales, products and engineering teams to ensure that customers’ expectations and experiences are met and delivered.  Computer Vision & NLP Applications: Lead initiatives applying ML/AI, computer vision, and natural language processing to extract data from unstructured documents (bank statements, financial statements, notes) to add new dimensions to credit analysis.  Generative AI & Advanced Risk Assessment: Spearhead the training and deployment of generative AI models, yielding sharper risk insights and enabling constructive, forward-looking data analysis.  Product Development Leadership: Collaborate with engineering and product teams to drive the integration of AI/ML into next-generation financial products and systems, ensuring solutions are tailored for the unique needs of the banking and lending industries.  Data Transformation & Reporting: Transform publicly available and internal data into actionable reports, alerts, triggers, and scorecards. Lead the development of automation tools and systems that streamline analysis and reduce manual workloads.  Business Requirements & Leadership: Drive complex, cross-functional requirements gathering, documentation (including PRDs), and project delivery. Engage in maintaining and prioritising Product backlog to accommodate business needs. Build and mentor high-performing teams, establish best-in-class processes, and foster a culture of operational excellence.  Communication & multi-tasking: Articulate complex concepts to diverse stakeholders. Expertly manage competing priorities and deliver quality results within tight deadlines, thriving in fast-paced, dynamic environments. Requirements  CFA Charter holder or equivalent advanced degree with relevant experience in financial analysis.  8+ years of experience in developing credit risk modelling, financial analysis, or related roles within banking, NBFC, or fintech organizations.  Prior experience in developing credit underwriting and risk assessment score cards/models using computer vision (CV), natural language processing (NLP), and generative AI will be preferred.  Deep knowledge of scorecard development, statistical techniques, and interpretability/significance of model outputs.  Proven hands-on expertise in AI/ML model development for credit underwriting, especially using Python, R, or similar platforms.  Track record of successful product development from prototype through launch stage, especially for credit and risk management solutions.  Strong project management, team leadership, and stakeholder engagement skills.  Excellent written and verbal communication skills.  Excellent Data analysis, data visualisation skills.

We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that is bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com. What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it? We understand that you are looking for growth and variety in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you. We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while you work with a team that is fueled by purpose. The combination of these will lead to a truly differentiated experience for you. If this excites you, then apply below. Role: Senior Analyst - Data Science Descriptions: We are looking for a results-driven and hands-on Lead Data Scientist / Analyst with 56 years of experience to lead analytical solutioning and model development in the pharmaceutical commercial analytics domain. The ideal candidate will play a central role in designing and deploying Decision Engine frameworks, implementing advanced analytics solutions, and mentoring junior team members. Key Responsibilities Partner with cross-functional teams and client stakeholders to gather business requirements and translate them into robust ML/analytical solutions. Design and implement Decision Engine workflows to support Next Best Action (NBA) recommendations in omnichannel engagement strategies. Analyze large and complex datasets across sources like APLD, sales, CRM, call plans, market share, patient claims, and segmentation data. Perform ad hoc and deep-dive analyses to address critical business questions across commercial and medical teams. Develop, validate, and maintain predictive models for use cases such as patient journey analytics, HCP targeting, sales forecasting, risk scoring, and marketing mix modeling. Implement MLOps pipelines using Dataiku, Git, and AWS services to support scalable and repeatable deployment of analytics models. Ensure data quality through systematic QC checks, test case creation, and validation frameworks. Lead and mentor junior analysts and data scientists in coding best practices, feature engineering, model interpretability, and cloud-based workflows. Stay up to date with industry trends, regulatory compliance, and emerging data science techniques relevant to life sciences analytics. Must Have 5 years of hands-on experience in pharmaceutical commercial analytics, with exposure to cross-functional brand analytics, omnichannel measurement, and ML modeling. At least 3 years of experience developing and deploying predictive models and ML pipelines in real-world settings. Proven experience with data platforms such as Snowflake, Dataiku, AWS, and proficiency in PySpark, Python, and SQL. Experience with MLOps practices, including version control, model monitoring, and automation. Strong understanding of pharmaceutical data assets (e.g., APLD, DDD, NBRx, TRx, specialty pharmacy, CRM, digital engagement). Proficiency in ML algorithms (e.g., XGBoost, Random Forest, SVM, Logistic Regression, Neural Networks, NLP). Experience in key use cases: Next Best Action, Recommendation Engines, Attribution Models, Segmentation, Marketing ROI, Collaborative Filtering. Hands-on expertise in building explainable ML models and using tools for model monitoring and retraining. Familiarity with dashboarding tools like Tableau or PowerBI is a plus. Strong communication and documentation skills to effectively convey findings to both technical and non-technical audiences. Ability to work in a dynamic, fast-paced environment and deliver results under tight timelines. EQUAL OPPORTUNITY Indegene is proud to be an Equal Employment Employer and is committed to the culture of Inclusion and Diversity. We do not discriminate on the basis of race, religion, sex, colour, age, national origin, pregnancy, sexual orientation, physical ability, or any other characteristics. All employment decisions, from hiring to separation, will be based on business requirements, the candidates merit and qualification. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristics. Locations - Bangalore, KA, IN Show more Show less

About Zupee We are the biggest online gaming company with largest market share in the Indian gaming sector’s largest segment — Casual & Boardgame. We make skill-based games that spark joy in the everyday lives of people by engaging, entertaining, and enabling earning while at play. In the three plus years of existence, Zupee has been on a mission to improve people’s lives by boosting their learning ability, skills, and cognitive aptitude through scientifically designed gaming experiences. Zupee presents a timeout from the stressful environments we live in today and sparks joy in the lives of people through its games. Zupee invests in people and bets on creating excellent user experiences to drive phenomenal growth. We have been running profitable at EBT level since Q3, 2020 while closing Series B funding at $102 million, at a valuation of $600 million. Zupee is all set to transform from a fast-growing startup to a firm contender for the biggest gaming studio in India. About The Job Role: Lead Data Scientist Reports to: Data Science Manager Location: Gurgaon Responsibilities: - Responsible for designing, developing, testing and deploying ML models that can leverage multiple signal sources, to build a personalized user experience. - Work closely with the business stakeholders to identify the potential Data science applications. - Contribute by doing opportunity analysis, building project proposals, designing and implementation of ML projects, in the areas of Ranking, Embeddings, Recommendation engines etc. - Collaborate with software engineering teams to design experiments, model implementations and new feature creation. - Clearly communicate technical details, strategies, and outcomes to a business audience. Requirements: - 7+ years of hands-on experience in data science using techniques including but not limited to regression, classification, NLP etc. - Previous experience in model deployment, model monitoring, optimization and model interpretability. - Expertise with Random forests, Gradient boosting, KNN, Regression and unsupervised learning algorithms - Experience in using Neural Networks like ANN, RNN, Reinforcement Learning or Deep Learning etc. - Solid understanding of Python and common machine learning frameworks such as XG Boost, scikit-learn, PyTorch / TensorFlow. - Outstanding problem-solving skills, with demonstrated ability to think creatively and strategically. - Technology-driven mindset, up to date with digital and technology literature, trends - S/he must have knowledge of Experimentation and Basic Statistics - S/he must have experience in Predictive Analytics. Show more Show less

About Zupee We are the biggest online gaming company with largest market share in the Indian gaming sector’s largest segment — Casual & Boardgame. We make skill-based games that spark joy in the everyday lives of people by engaging, entertaining, and enabling earning while at play. In the three plus years of existence, Zupee has been on a mission to improve people’s lives by boosting their learning ability, skills, and cognitive aptitude through scientifically designed gaming experiences. Zupee presents a timeout from the stressful environments we live in today and sparks joy in the lives of people through its games. Zupee invests in people and bets on creating excellent user experiences to drive phenomenal growth. We have been running profitable at EBT level since Q3, 2020 while closing Series B funding at $102 million, at a valuation of $600 million. Zupee is all set to transform from a fast-growing startup to a firm contender for the biggest gaming studio in India. About The Job Role: Senior Data Scientist Reports to: Data Science Manager Location: Gurgaon Responsibilities: - Responsible for designing, developing, testing and deploying ML models that can leverage multiple signal sources, to build a personalized user experience. - Work closely with the business stakeholders to identify the potential Data science applications. - Contribute by doing opportunity analysis, building project proposals, designing and implementation of ML projects, in the areas of Ranking, Embeddings, Recommendation engines etc - Collaborate with software engineering teams to design experiments, model implementations and new feature creation. - Clearly communicate technical details, strategies, and outcomes to a business audience Requirements: - 5+ years of hands-on experience in data science using techniques including but not limited to regression, classification, NLP etc. - Previous experience in model deployment, model monitoring, optimization and model interpretability. - Expertise with Random forests, Gradient boosting, KNN, Regression and unsupervised learning algorithms - Experience in using Neural Networks like ANN, RNN, Reinforcement Learning or Deep Learning etc. - Solid understanding of Python and common machine learning frameworks such as XG Boost, scikit-learn, PyTorch / Tensorflow - Outstanding problem-solving skills, with demonstrated ability to think creatively and strategically. - Technology-driven mindset, up to date with digital and technology literature, trends. - S/he must have knowledge of Experimentation and Basic Statistics. - S/he must have experience in Predictive Analytics. Show more Show less

interface.ai is the industry's-leading specialized AI provider for banks and credit unions, serving over 100 financial institutions. The company's integrated AI platform offers a unified banking experience through voice, chat, and employee-assisting solutions, enhanced by cutting-edge proprietary Generative AI. Our mission is clear: to transform the banking experience so every consumer enjoys hyper-personalized, secure, and seamless interactions, while improving operational efficiencies and driving revenue growth. interface.ai offers pre-trained, domain-specific AI solutions that are easy to integrate, scale, and manage, both in-branch and online. Combining this with deep industry expertise, interface.ai is the AI solution for banks and credit unions that want to deliver exceptional experiences and stay at the forefront of AI innovation. About Interface.ai interface.ai is the most advanced AI platform for financial institutions. We serve over 100 credit unions and community banks, enabling millions of intelligent conversations every day through voice, chat, and internal copilots. As a fast-growing, AI-native company, data is at the heart of how we build, measure, and scale our products. From intelligent conversation design to customer automation analytics, we apply machine learning and statistical modeling to deliver real-time, measurable outcomes. About The Role We are seeking a Senior Data Scientist to lead the development of scalable, production-grade models and analytics systems that power core platform that our Products run on This is a high-impact role where you'll work on problems at the intersection of language understanding, user behavior prediction, decision optimization, and platform-level intelligence . You will be embedded in product-driven teams, while also collaborating with infrastructure and research to shape the future of intelligence at interface.ai. Key Responsibilities Develop and deploy machine learning models for use cases like intent recognition, conversation scoring, outcome prediction, and next-best-action systems Design and run A/B and multivariate experiments to validate hypotheses and measure product impact Build real-time and batch inference pipelines in collaboration with engineering Define, instrument, and maintain data pipelines for user interaction modeling, longitudinal engagement, and behavioral segmentation Develop intelligence layers for customer-facing analytics products (e.g., AI explainability, task attribution, feature impact modeling) Partner with product managers, engineers, and UX teams to define data-informed product features Translate complex model outcomes into actionable insights for internal and external stakeholders Stay current with research and best practices in Voice models, decision modeling, time-series analysis, and agentic AI architectures What Success Looks Like Within your first 6–12 months, you will: Launch production-grade models that are actively used in product features or operations workflows Define and validate key behavioral or predictive models that influence roadmap direction Improve accuracy, performance, or interpretability of existing AI systems across voice and chat products Drive measurable lift in engagement, resolution rate, or automation through data-driven product iterations Collaborate across departments to establish trusted experimentation and measurement frameworks Required What You Bring 5+ years of experience in applied data science, including end-to-end model development and deployment Strong knowledge of Python, R, SQL, and experience with ML libraries such and deep learning frameworks. Experience with statistical testing, experiment design, and causal inference Understanding of production ML pipelines and collaboration with data engineering teams Experience with speech models, conversational systems, or classification models in user-facing applications Strong product thinking—able to translate model insights into product impact and roadmap trade-offs Preferred Experience working in B2C environments especially in regulated industries (e.g., financial services, healthcare) Exposure to retrieval-augmented generation (RAG), embedding-based search, or LLM evaluation frameworks Familiarity with tools like Airflow, MLflow, dbt, or feature stores Prior work in chatbots, IVRs, or user feedback systems Why Join Us Data science is central to our product innovation strategy You’ll have a direct, measurable impact on customer outcomes and platform intelligence You’ll work on real-world AI applications with scaled deployment and product visibility You’ll collaborate with a cross-disciplinary team of engineers, designers, and product leaders moving at startup speed At interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible. Show more Show less

We’re hiring an Applied AI Researcher in the deep-tech and AI research industry . We are seeking a highly skilled and motivated professional to join our advanced research team. In this role, you will design multi-agent architectures, develop domain-specific scaffolding techniques, and build evaluation frameworks for next-generation AI systems. You’ll work at the frontier of applied AI—combining LLMs, reinforcement learning, and multi-agent systems to build scalable and meaningful solutions. Key Responsibilities Architect and implement novel multi-agent systems that enable advanced problem-solving and collaboration Design domain-specific scaffolding techniques to tailor AI behavior to complex, real-world domains Curate and manage high-quality datasets for training and evaluation of AI models across scientific and industrial use cases Establish and iterate on robust evaluation frameworks to measure performance, alignment, and robustness Research and apply reinforcement learning techniques, including RLHF, DPO, GRPO, and others Explore post-training optimization, fine-tuning, and domain adaptation methods Collaborate cross-functionally with engineering and product teams to translate research into production-ready solutions Stay abreast of cutting-edge developments in AI and contribute to internal and external research communities Document and communicate findings through technical reports, presentations, and publications Required Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field 4+ years of experience in applied AI research or equivalent industry R&D experience Strong foundations in optimization, probability, and linear algebra Expertise in Python and frameworks like PyTorch or JAX Experience with RL and post-training methods (e.g., SFT, DPO, RLHF) Proficiency in building and aligning small language models (SLMs), including reasoning-specific models Familiarity with prompting strategies like Chain of Thought and dataset design for reasoning tasks Deep understanding of multi-agent systems and distributed training (multi-GPU/multi-node) Experience in designing evaluation metrics and performance analysis methodologies Preferred Experience Publications in leading ML conferences (NeurIPS, ICLR, ICML, AAMAS, etc.) Experience applying AI to scientific domains like drug discovery, chip design, or materials science Exposure to multimodal models and VLMs Experience with open-ended systems and emergent behavior in agent-based learning Background in computational science (chemistry, physics, EE, or applied math) Familiarity with MLOps, Kubernetes, Ray, Hydra, and MLflow Experience with domain adaptation, interpretability, and model optimization for deployment Contributions to open-source AI projects Expertise in building GPU-accelerated pipelines and optimizing inference at scale What We Offer Work on high-impact, frontier research with real-world applications Access to high-performance computing resources A collaborative, intellectually stimulating environment Autonomy to explore novel ideas aligned with our mission Competitive salary, benefits, and opportunities for growth Skills: Research,Design,Multi-agent Systems,Models Show more Show less