3498 Data Scientist Jobs - Page 37

As a Senior Data Science and Modeling Specialist at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Provide leadership, guidance, and support to team members, ensuring the successful completion of tasks, and promoting a positive work environment that fosters collaboration and productivity, taking responsibility of the whole team. Nice-to-have skills Qualifications Qualifications 4-6 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

As a Principle Engineer - Data Science and Modeling at Incedo, you will be responsible for developing and deploying predictive models and machine learning algorithms to support business decision-making. You will work with data scientists, data engineers, and business analysts to understand business requirements and develop data-driven solutions. You will be skilled in programming languages such as Python or R and have experience in data science tools such as TensorFlow or Keras. You will be responsible for ensuring that models are accurate, efficient, and scalable. Roles & Responsibilities: Developing and implementing machine learning models and algorithms to solve complex business problems Conducting data analysis and modeling using statistical and data analysis tools Collaborating with other teams to ensure the consistency and integrity of data Providing guidance and mentorship to junior data science and modeling specialists Presenting findings and recommendations to stakeholders Foster a collaborative and supportive work environment, promoting open communication and teamwork. Demonstrate strong leadership skills, with the ability to inspire and motivate team members to perform at their best. Technical Skills Skills Requirements: Proficiency in statistical analysis techniques such as regression analysis, hypothesis testing, or time-series analysis. Knowledge of machine learning algorithms and techniques such as supervised learning, unsupervised learning, or reinforcement learning. Experience with data wrangling and data cleaning techniques using tools such as Python, R, or SQL. Understanding of big data technologies such as Hadoop, Spark, or Hive. Must have excellent communication skills and be able to communicate complex technical information to non-technical stakeholders in a clear and concise manner. Must understand the company's long-term vision and align with it. Should be able to identify problems, generate effective solutions, and troubleshoot issues that may arise while working on complex projects. Must Display Adaptability to changing circumstances, new technology, and shifting priorities. Nice-to-have skills Qualifications Qualifications 11-12 years of work experience in relevant field B.Tech/B.E/M.Tech or MCA degree from a reputed university. Computer science background is preferred

Internship Raipur, Bengaluru Posted 2 months ago SUBHAG HEALTHTECH PVT LTD SUBHAG® HealthTech has developed a cutting-edge medical device that enables couples to perform Intra Uterine Insemination (IUI) discreetly in a home environment. This innovative solution aims to address male infertility issues without the need to visit a doctor, expanding infertility treatment through home-based IUI and disrupting the IVF market. With a focus on revolutionizing infertility treatment in India, SUBHAG® HealthTech is dedicated to providing comfortable and effective medical solutions to couples facing fertility challenges. Job Description Essential Responsibilities Create, analyze and maintain explanatory/predictive Data Science models using healthcare data in the Infertility segment Work with real-world case studies in Data Science and a chance to implement various modeling techniques Get real-life experience of working with big data in the digital marketing sphere. Opportunity to independently execute and lead analytical projects and assignments Help solve some challenging Healthcare related digital marketing problems globally. Transform business question into data requirements; collect and merge the data; analyse the data, link it to the business reality and present the results Develop predictive models and machine learning algorithms to study the change in physician prescribing behaviour, as well as Subhag Healthtech, integrated campaign response behaviour. Build analysis to understand user engagement and behaviors across various Subhag Healthtech products. Build expertise in data preparation, data visualisations and transformations through SAS, R, Tableau and other analytical tools. Required Qualifications Must have: B. Tech/B.E. / MSc Computer science/ Statistics/other relevant specialization from premier institutes 5 -7 years’ experience explicitly in Data Analytics – Design, Architecture and the software development lifecycle. Expertise in AWS compute, storage & Big data services EMR, Spark, Redshift, S3, Glue, Step Functions, Lambda serverless, EKS, SageMaker, Dynamo DB etc. Experience in one or more ETL like Informatica Experience in Data warehousing, Data & Dimensional modeling and concepts. Experience in one or more data visualization tool like Tableau, Spotfire etc. Good understanding of enterprise source systems ERP, CRM-etc. Experience in Python or Core Java, Java Web Services development with REST APIs Demonstrated ability to translate user needs and requirements into design alternatives Hands-on experience in Natural Language Processing and Deep Learning projects Experience in healthcare sector Requirement Knowledge of existing and potential clients and ensuring business growth opportunities in relation to company’s strategic plans. Well connected with Pharma/ Surgical Equipment Distributors, Hospitals, Doctors in the region Excellent knowledge of MS Office and using the Internet Familiarity with CRM practices along with ability to build productive business professional relationships Highly motivated and target driven with a proven track record in marketing Excellent marketing and communication skills Prioritizing, time management and organizational skills Relationship management skills and openness to feedback. To apply for this job email your details to [email protected]

Job Title: Data Scientist Location: [Insert Location] Experience: 5–10 years (flexible based on expertise) Employment Type: Full-Time Compensation: [Insert Budget / Competitive as per industry standards] About the Role: We are looking for a highly skilled and innovative Data Scientist with deep expertise in Machine Learning, AI, and Cloud Technologies to join our dynamic analytics team. The ideal candidate will have hands-on experience in NLP, LLMs, Computer Vision , and advanced statistical techniques, along with the ability to lead cross-functional teams and drive data-driven strategies in a fast-paced environment. Key Responsibilities: Develop and deploy end-to-end machine learning pipelines including data preprocessing, modeling, evaluation, and production deployment. Work on cutting-edge AI/ML applications such as LLM-finetuning, NLP, Computer Vision, Hybrid Recommendation Systems , and RAG/CAG techniques . Leverage platforms like AWS (SageMaker, EC2) and Databricks for scalable model development and deployment. Handle data at scale using Spark, Python, SQL , and integrate with NoSQL and Vector Databases (Neo4j, Cassandra) . Design interactive dashboards and visualizations using Tableau for actionable insights. Collaborate with cross-functional stakeholders to translate business problems into analytical solutions. Guide data curation efforts and ensure high-quality training datasets for supervised and unsupervised learning. Lead initiatives around AutoML, XGBoost, Topic Modeling (LDA/LSA), Doc2Vec , and Object Detection & Tracking . Drive agile practices including Sprint Planning, Resource Allocation, and Change Management . Communicate results and recommendations effectively to executive leadership and business teams. Mentor junior team members and foster a culture of continuous learning and innovation. Technical Skills Required: Programming: Python, SQL, Spark Machine Learning & AI: NLP, LLMs, Deep Learning, Computer Vision, Hybrid Recommenders Techniques: RAG, CAG, LLM-Finetuning, Statistical Modeling, AutoML, Doc2Vec Data Platforms: AWS (SageMaker, EC2), Databricks Databases: SQL, NoSQL, Neo4j, Cassandra, Vector DBs Visualization Tools: Tableau Certifications (Preferred): IBM Data Science Specialization Deep Learning Nanodegree (Udacity) SAFe® DevOps Practitioner Certified Agile Scrum Master Professional Competencies: Proven experience in team leadership, stakeholder management , and strategic planning . Strong cross-functional collaboration and ability to drive alignment across product, engineering, and analytics teams. Excellent problem-solving, communication, and decision-making skills. Ability to manage conflict resolution, negotiation , and performance optimization within teams.

Job Title Senior Data Scientist Data & Analytics How you will do it Advanced Analytics, LLMs & Modeling Design and implement advanced machine learning models including deep learning, time-series forecasting, recommendation engines, and LLM-based solutions (e. g. , GPT, LLaMA, Claude). Develop use cases around enterprise search, document summarization, conversational AI, and automated knowledge retrieval using large language models. Fine-tune or prompt-engineer foundation models (e. g. , OpenAI, Azure OpenAI, Hugging Face) for domain-specific applications. Evaluate and optimize LLM performance, latency, cost-effectiveness, and hallucination mitigation strategies for production use. Data Strategy & Engineering Collaboration Work closely with data and ML engineering teams to integrate LLM-powered applications into scalable, secure, and reliable pipelines. Contribute to the development of retrieval-augmented generation (RAG) architectures using vector databases (e. g. , FAISS, Azure Cognitive Search). Support the deployment of models using MLOps principles, ensuring robust monitoring and lifecycle management. Business Impact & AI Strategy Partner with cross-functional stakeholders to identify opportunities for applying LLMs and generative AI to solve complex business challenges. Lead workshops or proofs-of-concept to demonstrate value of LLM use cases across business units. Translate complex model outputs, including those from LLMs, into clear insights and decision support tools for non-technical audiences. Thought Leadership & Mentorship Act as an internal thought leader on AI and LLM innovation, keeping JCI at the forefront of industry advancements. Mentor and upskill data science team members in advanced AI techniques, including transformer models and generative AI frameworks. Contribute to strategic roadmaps for generative AI and model governance within the enterprise. Qualifications & Experience Education in Data Science, Artificial Intelligence, Computer Science, or related quantitative discipline. 5+ years of hands-on experience in data science, including at least 1 2 years working with LLMs or generative AI technologies. Demonstrated success in deploying machine learning and NLP solutions at scale. Proven experience with cloud AI platforms especially Azure OpenAI, Azure ML, Hugging Face, or AWS Bedrock. Technical Expertise Proficiency in Python and SQL, including libraries like Transformers (Hugging Face), LangChain, PyTorch, and TensorFlow. Experience with prompt engineering, fine-tuning, and LLM orchestration tools. Familiarity with data storage, retrieval systems, and vector databases. Strong understanding of model evaluation techniques for generative AI, including factuality, relevance, and toxicity metrics. Leadership & Soft Skills Strategic thinker with a strong ability to align AI initiatives to business goals. Excellent communication and storytelling skills, especially in articulating the value of LLMs and advanced analytics. Strong collaborator with a track record of influencing stakeholders across product, engineering, and executive teams. Preferred Qualifications Experience with IoT, edge analytics, or smart building systems. Familiarity with LLMOps, LangChain, Semantic Kernel, or similar orchestration frameworks. Knowledge of data privacy and governance considerations specific to LLM usage in enterprise environments.

Job Description Proficiency with Python (Pandas, NumPy), SQL, and Java. Experience with LLMs, LangChain, and Generative AI technologies. Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka). Microservices, CI CD, ML Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders. Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools. Knowledge in Machine Learning, NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. Work in a team/ Independently. Excellent Written Verbal Communication Skills Solid critical thinking and questioning skills. High degree of flexibility - willing to fill in the gaps rather than relying on others Strong communication skills, especially in presenting data insights. Flexibility, problem-solving, and a proactive approach in a fast-paced environment

Rockwell Automation is a global technology leader focused on helping the world s manufacturers be more productive, sustainable, and agile. With more than 28, 000 employees who make the world better every day, we know we have something special. Behind our customers - amazing companies that help feed the world, provide life-saving medicine on a global scale, and focus on clean water and green mobility - our people are energized problem solvers that take pride in how the work we do changes the world for the better. We welcome all makers, forward thinkers, and problem solvers who are looking for a place to do their best work. And if that s you we would love to have you join us! Job Description Summary: Collaborate with engineers, product managers, and operations leaders to build predictive maintenance models, improve manufacturing throughput, and drive cost savings. Work on anomaly detection, quality control, and forecasting use cases within our IIoT platform. You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model. Your Responsibilities: Design and implement scalable ETL pipelines and ML workflows using platforms like AzureML, AWS SageMaker. Develop and deploy time-series models for forecasting and anomaly detection. Apply classical ML techniques such as regression, decision trees, clustering, and deep learning to solve business problems. Collaborate with cross-functional teams to translate business requirements into data science solutions. Contribute to model monitoring, performance tuning, and continuous improvement. You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model. The Essentials - You Will Have: 1 2 years of experience in data science or machine learning roles. Proven experience with cloud ML platforms (AzureML, SageMaker, or equivalent). Strong understanding and hands-on experience with time-series modeling and forecasting techniques. Solid foundation in classical ML algorithms (e. g. , regression, decision trees, clustering, deep learning). Proficiency in Python, SQL, and ML libraries such as scikit-learn, TensorFlow, or PyTorch. Experience building and maintaining ETL pipelines for large-scale data processing. The Preferred - You Might Also Have: Familiarity with BI tools (Tableau, Looker, Power BI) and MLOps frameworks (MLflow, Kubeflow). Familiarity with FastAPI for building and deploying model serving endpoints. Familiarity working with in Linux Environments. What We Offer: Our benefits package includes Comprehensive mindfulness programs with a premium membership to Calm Volunteer Paid Time off available after 6 months of employment for eligible employees. Company volunteer and donation matching program Your volunteer hours or personal cash donations to an eligible charity can be matched with a charitable donation. Employee Assistance Program Personalized wellbeing programs through our OnTrack program On-demand digital course library for professional development At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if youre excited about this role but your experience doesnt align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles. #LI-Hybrid #LI-FR1

We have an exciting opportunity for you to leverage data science methods to deliver actionable insights across the Card business. As a Data Science Associate within the Card Data and Analytics team, you will leverage skills in building insights from advanced analytics, Gen AI / LLM tools, analysis, data querying, and extracting insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, and machine learning/AI, proficiency in SQL/Python programming, visualization methods, and technologies. Job Responsibilities Leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics for the Credit Card business. Support development of data science / AIML use cases for the Card business. Help partners in the Card business define their business problems and scope analytical solutions. Build an in-depth understanding of the Card domain and available data assets. Research, design, implement, and evaluate analytical approaches and models. Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets. Communicate findings and obstacles to stakeholders to drive delivery to market. Required Qualifications, Capabilities, and Skills Bachelor s degree in a relevant quantitative field required in an analytical field (e. g. , Statistics, Economics, Applied Math, Operations Research, other Data Science fields). 4+ years of hands-on experience with data analytics; experience evaluating complex business problems and devising recommendations. Exceptional analytical, quantitative, problem-solving, and communication skills. Excellent leadership, consultative partnering, and collaboration across teams. Knowledge of statistical software packages (e. g. , Python) and data querying languages (e. g. , SQL). Experience across a broad range of modern analytics tools (e. g. , Snowflake, Databricks, SQL, Spark, Python). Preferred Qualifications, Capabilities, and Skills Understanding of the key drivers within the credit card P&L is preferred. Financial services background preferred, but not required. Master s degree or equivalent in an analytical field. We have an exciting opportunity for you to leverage data science methods to deliver actionable insights across the Card business. As a Data Science Associate within the Card Data and Analytics team, you will leverage skills in building insights from advanced analytics, Gen AI / LLM tools, analysis, data querying, and extracting insights from big data to support our Credit Card business. This role is a hands-on mix of consulting know-how, analytical proficiency in statistics, data science, and machine learning/AI, proficiency in SQL/Python programming, visualization methods, and technologies. Job Responsibilities Leverage your knowledge and analytical skills to uncover novel use cases of Big Data analytics for the Credit Card business. Support development of data science / AIML use cases for the Card business. Help partners in the Card business define their business problems and scope analytical solutions. Build an in-depth understanding of the Card domain and available data assets. Research, design, implement, and evaluate analytical approaches and models. Perform ad-hoc exploratory analyses and data mining tasks on diverse datasets. Communicate findings and obstacles to stakeholders to drive delivery to market. Required Qualifications, Capabilities, and Skills Bachelor s degree in a relevant quantitative field required in an analytical field (e. g. , Statistics, Economics, Applied Math, Operations Research, other Data Science fields). 4+ years of hands-on experience with data analytics; experience evaluating complex business problems and devising recommendations. Exceptional analytical, quantitative, problem-solving, and communication skills. Excellent leadership, consultative partnering, and collaboration across teams. Knowledge of statistical software packages (e. g. , Python) and data querying languages (e. g. , SQL). Experience across a broad range of modern analytics tools (e. g. , Snowflake, Databricks, SQL, Spark, Python). Preferred Qualifications, Capabilities, and Skills Understanding of the key drivers within the credit card P&L is preferred. Financial services background preferred, but not required. Master s degree or equivalent in an analytical field.

Candidate Candidate LTIMindtree Hiring for Data Scientist (GEN AI) Location: Pan India Experience: 8 to 16 years Mandatory Skills - Data Scientist, Machine Learning, Deep learning, GEN AINotice Period - Immediate to 45 days of NP Job Description : Job descriptionWe are looking for a highly skilled and results-driven Experienced Data Scientist to be at the forefront of developing and implementing Generative AI solutions that address critical business challenges and unlock new opportunities. This individual will leverage their deep expertise in data science, machine learning, and specifically Generative AI techniques to drive impactful projects from ideation to deployment. They will develop AI & ML solutions to tackle complex business challenges and facilitate data-driven decision-making through hands-on work with large datasets and strong collaboration with cross-functional teams to deliver significant results. Responsibilities: Data Handling & Preparation: Work with diverse and large-scale datasets. Perform data cleaning, preprocessing, feature engineering, and create synthetic datasets as needed for training and evaluating Generative AI models. Ensure data quality and integrity throughout the model development lifecycle. Model Optimization & Deployment: Optimize Generative AI models for performance, scalability, efficiency, and responsible AI considerations (bias detection and mitigation, hallucination reduction). Collaborate with Machine Learning Engineers and DevOps teams to deploy models into production environments and establish monitoring frameworks. Prompt Engineering & Fine-tuning: Develop effective prompts and fine-tuning strategies for Large Language Models to achieve desired outputs and adapt models to specific domains and tasks. Generative AI Model Development & Implementation: Design, develop, train, fine-tune, and deploy various Generative AI models, including but not limited to Large Language Models (LLMs), diffusion models, Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs), for applications If Interested , Kindly share me your updated CV with below details - Pramoth@ltimindtree.com Candidate Name - Candidate Email ID - Candidate Mobile Number - Total Years of IT experience - Relevant Years of Data Scientist Experience - Current CTC - Expected CTC - Any Offers in hand or Pipeline - Notice Period (If serving then LWD)-

Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities • Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. • Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills • Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills.

Remote Work: Hybrid Overview: At Zebra, we are a community of innovators who come together to create new ways of working to make everyday life better. United by curiosity and care, we develop dynamic solutions that anticipate our customer s and partner s needs and solve their challenges. Being a part of Zebra Nation means being seen, heard, valued, and respected. Drawing from our diverse perspectives, we collaborate to deliver on our purpose. Here you are a part of a team pushing boundaries to redefine the work of tomorrow for organizations, their employees, and those they serve. You have opportunities to learn and lead at a forward-thinking company, defining your path to a fulfilling career while channeling your skills toward causes that you care about locally and globally. We ve only begun reimaging the future for our people, our customers, and the world. Let s create tomorrow together. We are seeking a highly skilled and motivated Data Scientist (LLM Specialist) to join our AI/ML team. This role is ideal for an individual passionate about Large Language Models (LLMs) , workflow automation, and customer-centric AI solutions. You will be responsible for building robust ML pipelines , designing scalable workflows, interfacing with customers, and independently driving research and innovation in the evolving agentic AI space . Key Responsibilities: LLM Development & Optimization: Train, fine-tune, evaluate, and deploy Large Language Models (LLMs) for various customer-facing applications. Pipeline & Workflow Development: Build scalable machine learning workflows and pipelines that facilitate efficient data ingestion, model training, and deployment. Model Evaluation & Performance Tuning: Implement best-in-class evaluation metrics to assess model performance, optimize for efficiency, and mitigate biases in LLM applications. Customer Engagement: Collaborate closely with customers to understand their needs, design AI-driven solutions , and iterate on models to enhance user experiences. Research & Innovation: Stay updated on the latest developments in LLMs, agentic AI , reinforcement learning with human feedback (RLHF), and generative AI applications. Recommend novel approaches to improve AI-based solutions. Infrastructure & Deployment: Work with MLOps tools to streamline deployment and serve models efficiently using cloud-based or on-premise architectures, including Google Vertex AI for model training, deployment, and inference. Foundational Model Training: Experience working with open-weight foundational models , leveraging pre-trained architectures, fine-tuning on domain-specific datasets, and optimizing models for performance and cost-efficiency. Cross-Functional Collaboration: Partner with engineering, product, and design teams to integrate LLM-based solutions into customer products seamlessly. Ethical AI Practices: Ensure responsible AI development by addressing concerns related to bias, safety, security, and interpretability in LLMs. Responsibilities: Experience: experience in ML, NLP, or AI-related roles, with a focus on LLMs and generative AI . Programming Skills: Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch LLM Expertise: Hands-on experience in training, fine-tuning, and deploying LLMs (e.g., OpenAI s GPT, Meta s LLaMA, Mistral, or other transformer-based architectures). Foundational Model Knowledge: Strong understanding of open-weight LLM architectures , including training methodologies, fine-tuning techniques, hyperparameter optimization, and model distillation . Data Pipeline Development: Strong understanding of data engineering concepts , feature engineering, and workflow automation using Airflow or Kubeflow . Cloud & MLOps: Experience deploying ML models in cloud environments like AWS, GCP (Google Vertex AI), or Azure using Docker and Kubernetes . Model Serving & Optimization: Proficiency in model quantization, pruning, distillation, and knowledge distillation to improve deployment efficiency and scalability. Research & Problem-Solving: Ability to conduct independent research , explore novel solutions , and implement state-of-the-art ML techniques. Strong Communication Skills: Ability to translate technical concepts into actionable insights for non-technical stakeholders. Version Control & Collaboration: Proficiency in Git, CI/CD pipelines , and working in cross-functional teams . Qualifications: Bachelor s in Computer Science, Machine learning, or related discipline.Master s preferred Strong background in statistics, machine learning, deep learning and programming necessary. 5+years experience required Experience in solving large-scale real-world industry problems, preferably in collaboration with cross-functional, multi-disciplinary teams Knowledge of statistical programming techniques and languages (e.g., R, Python, Java, etc.) Working knowledge of common machine learning and deep learning approaches (e.g. regression, clustering, classification, dimensionality reduction, supervised and unsupervised techniques, Bayesian reasoning, boosting, random forests, deep learning) and data analysis packages (e.g. scikit-learn, pyclustering, pathways analysis, MLlib) Prior experience with Tensorflow Prior experience in Natural Language Processing using NLTK Retail industry experience desired Experience using cloud compute (e.g. Google Cloud Platform, AWS, Azure) Familiarity with NoSQL databases, graphical analyses, and large-scale data processing frameworks (e.g. Apache Spark) Solid understanding of data structures, software design and architecture Ability to work independently and take initiative, but also a co-operative team player To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department. ", "

Data Scientist for Market Research Job Description : Role Overview: We are seeking a highly skilled Data Scientist with strong analytical programming capabilities and experience working with large-scale datasets The role involves driving analytics-led market estimations, model development using LLMs, and supporting new product initiatives Key Responsibilities: Clean, process, and analyze large datasets for actionable insights and market extrapolations Develop and deploy AI/ML models, including use of LLMs for market intelligence automation and new product development Support the development of analytics modules and tools aligned to business and client needs Apply statistical and predictive modeling to generate actionable insights for client decision-making Candidate Profile : Required Qualifications: Bachelor s degree in Statistics, Computer Science, Data Science, or related fields 2-3 years of relevant experience a must Strong programming skills in Python and SQL Experience with AI/ML frameworks such as TensorFlow, PyTorch, and LLM-based workflows Familiarity with cloud platforms (AWS, GCP) and model deployment practices Tier 1/Tier 2 academic background preferred

The Data Scientist role at Scienaptic will enable you to be at the forefront of latest cutting- edge technology and create a significant and visible business impact for Scienaptic. You will be working with some of the best-in-class Engineers, Data Scientists, and Business Analytics Consultants in an environment which will encourage you to contribute widely to functional and technological aspects without worrying about conventional job silos. Responsibilities Design, develop, and deploy machine learning based models for credit risk and related use cases. Present model outcomes and recommendations to internal and external stakeholders. Establish a regular cadence of client engagement including roadmap planning, updates, and reporting. Establish model monitoring, back-testing, and performance tracking frameworks. Work closely with internal teams including Client Engagement, Engineering and Product to ensure smooth integration and deployment. Skills & Competencies 4+ years of experience in data science and machine learning with prior experience in credit risk model development. Strong proficiency in Python for data analysis and model development. Sound knowledge of supervised and unsupervised machine learning techniques. Strong communication and presentation skills - ability to explain complex models to stakeholders. Experience managing client relationships or working in a consulting environment Bachelor/master s degree in a quantitative discipline (e.g., Statistics, Economics,

We are looking for a highly skilled and experienced Data Scientist to join our Common Data Model (CDM) team within the Data Science and Credit Risk function. This role is pivotal in ensuring the integrity, scalability, and performance of our credit risk models by developing, maintaining, and quality-controlling the input mapping and data rollup logic that powers our decisioning infrastructure. As a senior member of the team, you will lead a small team of data scientists and collaborate closely with engineering, product, and integration teams to translate various data sources into standardized features used in risk models and strategies. Responsibilities Own the design, development, and maintenance input mapper and rollup logic for credit bureau, core banking, internal datasets and any additional data sources in the future. Ensure accuracy, performance, and compliance through rigorous QC frameworks and automated validation tools. Collaborate with credit risk, product, engineering, and integration teams to deploy and support model and strategy features in production environments. Analyse complex datasets and derive accurate business logic in alignment with credit policy and model requirements. Lead and mentor a team of data scientists and analysts, ensuring adherence to best practices in software engineering and data science. Contribute to data governance, documentation, and version control of the CDM and associated tooling. Skills & Competencies 5+ years of experience in Data Science/Data Engineering/Analytics Strong Python skills ability to writing clean, testable, modular, and production-grade code. Experience in credit risk, fintech, or financial services domains. Experience working on US credit bureau data Prior experience managing or mentoring technical teams. Strong communication skills and the ability to work cross-functionally with engineers, product managers, and stakeholders. Bachelor s / master s degree in a quantitative discipline (e.g. Engineering, Computer Science, Mathematics). Scienaptic is on a mission to increase credit availability by transforming technology used in credit decisioning. Over 150 years of credit experience is embedded in Scienaptic s AI native credit decision platform. Our clients across banks, credit unions, fintech, and other lenders use the platform to constantly improve the quality of underwriting decisions. This enables them to say yes to borrowers more often and faster.

Responsibilities Position responsibilities and expectations Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown, Power Point, Excel etc. Ability to learn new scripting language or analytics platform. Technical Skills required (must have) HandsOn Exposure to Generative AI (Design, development of GenAI application in production) Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. Strong understanding of deploying and optimizing AI application in production. Strong knowledge of statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Nonparametric analysis. Strong knowledge of DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) Strong knowledge of SQL and R/Python and experience with distribute data/computing tools/IDEs. Experience in advanced Text Analytics (NLP, NLU, NLG). Strong handson experience of endtoend statistical model development and implementation Understanding of LLMOps, ML Ops for scalable ML development. Basic understanding of DevOps and deployment of models into production (PyTorch, TensorFlow etc.). Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. Exposure to Cloud Platform (Azure or AWS or GCP) technologies and services like Azure AI/ Sage maker/Vertex AI, Auto ML, Azure Index, Azure Functions, OCR, OpenAI, storage, scaling etc. Technical Skills required (Any one or more) Experience in video/ image analytics (Computer Vision) Experience in IoT/ machine logs data analysis Exposure to data analytics platforms like Domino Data Lab, c3.ai, H2O, Alteryx or KNIME Expertise in Cloud analytics platforms (Azure, AWS or Google) Experience in Process Mining with expertise in Celonis or other tools Proven capability in using Generative AI services like OpenAI, Google (Gemini) Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) Understanding of finetuning for pretrained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique. Proven capability in building customized models from opensource distributions like Llama, Stable Diffusion Mandatory skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Preferred skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Years of experience required 36 Years Education qualification BE, B. Tech, M. Tech, M. Stat, Ph.D., M.Sc. (Stats / Maths) Education Degrees/Field of Study required Doctor of Philosophy, Bachelor of Engineering, Bachelor of Technology Degrees/Field of Study preferred Required Skills Chatbots, Data Structures, Generative AI Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, C++ Programming Language, Communication, Complex Data Analysis, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Machine Learning, Machine Learning Libraries, Named Entity Recognition, Natural Language Processing (NLP), Natural Language Toolkit (NLTK) {+ 20 more} Travel Requirements Government Clearance Required?

Not Applicable Specialism Data, Analytics & AI Management Level Associate & Summary 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 decisionmaking 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 decisionmaking and automation. At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purposeled and valuesdriven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . Responsibilities Position responsibilities and expectations Designing and building analytical /DL/ ML algorithms using Python, R and other statistical tools. Strong data representation and lucid presentation (of analysis/modelling output) using Python, R Markdown, Power Point, Excel etc. Ability to learn new scripting language or analytics platform. Technical Skills required (must have) HandsOn Exposure to Generative AI (Design, development of GenAI application in production) Strong understanding of RAG, Vector Database, Lang Chain and multimodal AI applications. Strong understanding of deploying and optimizing AI application in production. Strong knowledge of statistical and data mining techniques like Linear & Logistic Regression analysis, Decision trees, Bagging, Boosting, Time Series and Nonparametric analysis. Strong knowledge of DL & Neural Network Architectures (CNN, RNN, LSTM, Transformers etc.) Strong knowledge of SQL and R/Python and experience with distribute data/computing tools/IDEs. Experience in advanced Text Analytics (NLP, NLU, NLG). Strong handson experience of endtoend statistical model development and implementation Understanding of LLMOps, ML Ops for scalable ML development. Basic understanding of DevOps and deployment of models into production (PyTorch, TensorFlow etc.). Expert level proficiency algorithm building languages like SQL, R and Python and data visualization tools like Shiny, Qlik, Power BI etc. Exposure to Cloud Platform (Azure or AWS or GCP) technologies and services like Azure AI/ Sage maker/Vertex AI, Auto ML, Azure Index, Azure Functions, OCR, OpenAI, storage, scaling etc. Technical Skills required (Any one or more) Experience in video/ image analytics (Computer Vision) Experience in IoT/ machine logs data analysis Exposure to data analytics platforms like Domino Data Lab, c3.ai, H2O, Alteryx or KNIME Expertise in Cloud analytics platforms (Azure, AWS or Google) Experience in Process Mining with expertise in Celonis or other tools Proven capability in using Generative AI services like OpenAI, Google (Gemini) Understanding of Agentic AI Framework (Lang Graph, Auto gen etc.) Understanding of finetuning for pretrained models like GPT, LLaMA, Claude etc. using LoRA, QLoRA and PEFT technique. Proven capability in building customized models from opensource distributions like Llama, Stable Diffusion Mandatory skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Preferred skill sets AI chatbots, Data structures, GenAI objectoriented programming, IDE, API, LLM Prompts, Streamlit Years of experience required 36 Years Education qualification BE, B. Tech, M. Tech, M. Stat, Ph.D., M.Sc. (Stats / Maths) Education Degrees/Field of Study required Doctor of Philosophy, Bachelor of Engineering, Bachelor of Technology Degrees/Field of Study preferred Required Skills Chatbots, Data Structures, Generative AI Accepting Feedback, Accepting Feedback, Active Listening, AI Implementation, C++ Programming Language, Communication, Complex Data Analysis, Data Analysis, Data Infrastructure, Data Integration, Data Modeling, Data Pipeline, Data Quality, Deep Learning, Emotional Regulation, Empathy, GPU Programming, Inclusion, Intellectual Curiosity, Java (Programming Language), Machine Learning, Machine Learning Libraries, Named Entity Recognition, Natural Language Processing (NLP), Natural Language Toolkit (NLTK) {+ 20 more} Travel Requirements Government Clearance Required?

Why Join Us To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win. We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge technology to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential to driving our success. Why Join Us To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated, and we believe that when one of us wins, we all win. We offer a full benefits package, including exciting travel perks, generous time off, parental leave, a global hybrid work setup (with some pretty cool offices), and career development resources. All of this is designed to fuel our employees passion for travel and ensure a rewarding career journey. We re building a more open world. Join us. About the role Are you passionate about data, analytics, and collaborating with top talent to tackle complex problemsIf youre motivated to make an immediate impact on reimagining travel through insightful recommendations that drive improvements, we want to speak with you! We are seeking an experienced analytics professional to join our AI Agent Product Analytics Team, supporting a portfolio of some of the world s leading online travel brands. This is a mid-level individual contributor role, partnering with product managers and focusing on user experience optimization via GenAI-driven personalization. As a Data Scientist, you ll collaborate with a multidisciplinary team to solve a wide range of problems. You will bring scientific rigor and statistical methods to the challenges of business growth and product development. This role supports key business decisions throughout the product development lifecycle to improve the user experience for millions of Expedia customers. You ll be responsible for uncovering customer friction points, hypothesis generation and prioritization, experiment design, unbiased test analysis, actionable recommendations, and product optimization. If you are a self-starter who has demonstrated success using analytics to drive innovation and user engagement, this role is for you. In this role you will Apply expertise in quantitative analysis, machine learning, data mining, and data visualization to improve customer experience and business outcomes, with a focus on impactful analytics Guide product teams to actionable insights Own end-to-end testing excellence, including evaluating A/B and multivariate (MVT) tests, identifying opportunities, and recommending new features for test-and-learn initiatives Evaluate and apply alternative methods to supplement randomized testing Develop metrics frameworks for your product; build accurate, user-friendly dashboards/reports; and collaborate on goal setting, performance reviews, and strategic planning Take initiative to identify current and potential problems and recommend optimal solutions based on trade-offs Experience and qualifications 4+ years of experience in quantitative analysis to solve business problems Bachelor s degree in a science, technology, engineering, or mathematics (STEM) field Strong analytical skills, with the ability to break down complex business scenarios Experience with large datasets and proficiency in SQL or programming languages such as R or Python Excellent communicator with the ability to tell compelling stories using data Solid understanding of statistics and hypothesis testing (e.g., confidence intervals, regression, time series, clustering, factor analysis) Experience with visualization tools (e.g., Tableau) Familiarity with Adobe Analytics or Google Analytics is a plus Detail-oriented with a strong curiosity and passion for making an impact Accommodation requests If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request . We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. Expedia Groups family of brands includes: Brand Expedia , Hotels.com , Expedia Partner Solutions, Vrbo , trivago , Orbitz , Travelocity , Hotwire , Wotif , ebookers , CheapTickets , Expedia Group Media Solutions, Expedia Local Expert , CarRentals.com , and Expedia Cruises . 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50 Employment opportunities and job offers at Expedia Group will always come from Expedia Group s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs . Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.

Collaborate with engineers, product managers, and operations leaders to build predictive maintenance models, improve manufacturing throughput, and drive cost savings. Work on anomaly detection, quality control, and forecasting use cases within our IIoT platform. You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model. Your Responsibilities: Design and implement scalable ETL pipelines and ML workflows using platforms like AzureML, AWS SageMaker. Develop and deploy time-series models for forecasting and anomaly detection. Apply classical ML techniques such as regression, decision trees, clustering, and deep learning to solve business problems. Collaborate with cross-functional teams to translate business requirements into data science solutions. Contribute to model monitoring, performance tuning, and continuous improvement. You will report to Lead Sr Solution Architect of the function and will work from our Electronics City, Bengaluru Office in Hybrid work model. The Essentials - You Will Have: 1 2 years of experience in data science or machine learning roles. Proven experience with cloud ML platforms (AzureML, SageMaker, or equivalent). Strong understanding and hands-on experience with time-series modeling and forecasting techniques. Solid foundation in classical ML algorithms (e.g., regression, decision trees, clustering, deep learning). Proficiency in Python, SQL, and ML libraries such as scikit-learn, TensorFlow, or PyTorch. Experience building and maintaining ETL pipelines for large-scale data processing. The Preferred - You Might Also Have: Familiarity with BI tools (Tableau, Looker, Power BI) and MLOps frameworks (MLflow, Kubeflow). Familiarity with FastAPI for building and deploying model serving endpoints. Familiarity working with in Linux Environments. What We Offer: Our benefits package includes Comprehensive mindfulness programs with a premium membership to Calm Volunteer Paid Time off available after 6 months of employment for eligible employees. Company volunteer and donation matching program Your volunteer hours or personal cash donations to an eligible charity can be matched with a charitable donation. Employee Assistance Program Personalized wellbeing programs through our OnTrack program On-demand digital course library for professional development At Rockwell Automation we are dedicated to building a diverse, inclusive and authentic workplace, so if youre excited about this role but your experience doesnt align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right person for this or other roles. #LI-Hybrid #LI-FR1 Rockwell Automation s hybrid policy aligns that employees are expected to work at a Rockwell location at least Mondays, Tuesdays, and Thursdays unless they have a business obligation out of the office.

We are eagerly seeking candidates with 3 to 12 years’ experience for a Data Scientist to join our dynamic team. The ideal candidate will play a pivotal role in data analysis, statistical modeling, and machine learning to extract valuable insights from data Role: Data Scientist Location: Pune/Hyderabad/Mumbai Experience: 3 to 12 years Job type: Full time Work type: Hybrid Impact you will realize: Job Responsibilities Individuals will be responsible for leveraging their expertise in data analysis, statistical modeling, and machine learning to extract valuable insights from data Conduct in-depth data analysis to identify trends, patterns and anomalies in large datasets using tools like Python, SQL. Develop solutions using Machine Learning and Generative AI Develop and apply statistical models to gain insights and make predictions based on historical data. Build, train and deploy machine learning models for various applications, such as predictive modeling, customer segmentation, demand/sales forecasting, predictive maintenance etc. Assess model performance, iterate on models and fine-tune hyperparameters to optimize predictive accuracy and generalization. Deploy machine learning models into production systems and make necessary updates or improvements. Ensure data privacy and compliance with relevant regulations Documentation of analytical methods, data pipelines, and model workflows Key skills you will require: Primary Skills Conduct in-depth data analysis to identify trends, patterns and anomalies in large datasets using tools like Python, SQL. Develop solutions using Machine Learning and Generative AI Develop and apply statistical models to gain insights and make predictions based on historical data. Build, train and deploy machine learning models for various applications, such as predictive modeling, customer segmentation, demand/sales forecasting, predictive maintenance etc. Assess model performance, iterate on models and fine-tune hyperparameters to optimize predictive accuracy and generalization. Deploy machine learning models into production systems and make necessary updates or improvements. Ensure data privacy and compliance with relevant regulations Documentation of analytical methods, data pipelines, and model workflows

Data Scientist- ( Lead) - J49417 Proficiency with Python (Pandas, NumPy), SQL, and Java. Experience with LLMs, LangChain, and Generative AI technologies. Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka). Microservices, CI CD, ML Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders. Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools. Knowledge in Machine Learning, NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. Work in a team/ Independently. Excellent Written & Verbal Communication Skills Solid critical thinking and questioning skills. High degree of flexibility - willing to fill in the gaps rather than relying on others Strong communication skills, especially in presenting data insights. Flexibility, problem-solving, and a proactive approach in a fast-paced environment Qualification -BA,BBA,BBA/BMS,BBI,BCA,BCom,BCS,BDES,BE-Comp/IT,BEd,BE-Other,BFA,BFM,BIS,BIT,BMS,BSc-Comp/IT,BSc-Other,BTech-Comp/IT,BTech-Other,CA,CS,DCA,DCS,DE-Comp/IT,DE-Other,Diploma,ICWA,LLB, MA,MBA,MBBS, MCA,MCM,MCom,MCS,ME-Comp/IT,ME-Other,MIS,MIT,MMS,MSc-Comp/IT,MS-Comp/IT

Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills.

Job Description: We are looking for a talented and experienced Senior Data Scientist with a minimum of 4 years of professional experience in model development and expertise in Gen AI projects. As a Senior Data Scientist, you will be responsible for developing advanced machine learning models, conducting exploratory data analysis (EDA), performing feature selection/reduction, and utilizing cutting-edge technologies to deliver high-quality solutions. The ideal candidate should possess strong programming proficiency in Python and experience with cloud platforms like GCP or equivalent, as well as visualization tools like Qliksense, Power BI, Looker Studio, or Tableau. Job Responsibility: Data Scientists 4+ Year (Mandatory Skills) Model development (regression and classification), should have strong experience in performing EDA, Feature selection/Feature Reduction, building models and evaluate its performance Should have worked on Gen AI project Strong programming proficiency in python with mastery of data science libraries Pandas, numpy and scikitlearn GCP (BQ, Vertex AI) or other equivalent cloud Visualization (Qliksense / Looker Studio / Power BI / Tableau) Skills: GenAI Model development (regression and classification) EDA Python GCP / other equivalent cloud Visualization Data Scientist We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

The Senior Data Science Engineer will leverage advanced data science techniques to solve complex business problems, guide decision-making processes, and mentor junior team members. This role requires a combination of technical expertise in data analysis, machine learning, and project management skills. Responsibilities Data Analysis and Modeling: Analyze large-scale telecom datasets to extract actionable insights and build predictive models for network optimization and customer retention. Conduct statistical analyses to validate models and ensure their effectiveness. Machine Learning Development: Design and implement machine learning algorithms for fraud detection, churn prediction, and network failure analysis. Telecom-Specific Analytics: Apply domain knowledge to improve customer experience by analyzing usage patterns, optimizing services, and predicting customer lifetime value. ETL Processes: Develop robust pipelines for extracting, transforming, and loading telecom data from diverse sources. Collaboration: Work closely with data scientists, software engineers, and telecom experts to deploy solutions that enhance operational efficiency. Data Governance: Ensure data integrity, privacy, security and compliance with industry standards Qualifications Advanced degree in Data Science, Statistics, Computer Science, or a related field. Extensive experience in data science roles with a strong focus on machine learning and statistical modeling. Proficiency in programming languages such as Python or R and strong SQL skills. Familiarity with big data technologies (e.g., Hadoop, Spark) is advantageous. Expertise in cloud platforms such as AWS or Azure.

Role Summary: We are looking for an accountable, multitalented candidate to facilitate the operations. The computer vision consultant must be able to develop, implement and deploy ML functions across functions. The candidate should be adept at leading and conducting independent project work using the state-of-the-art deep learning technology, as well as participate in the transfer of knowledge from research to industry. The consultant will also have to collaborate with internal team and clients, to ensure that their approach meets the needs of each project. He/she should be able to deliver results according to project schedules while maintaining quality standards. The candidate will also be responsible to contribute towards organizational initiatives. Job Requirement Job Responsibilities: 1. Substantial hands-on experience with data handling. Capable of managing large volumes of data, extract, clean and comprehend 2. Able to analyze data independently and draw out salient insights. Able to define workflow for oneself and associates on a daily or periodic basis, contingent on the requirements of the project 3. Able to contribute meaningfully to brainstorming discussions around nuances of the project 4. Skilled in CNN or RNN or Feed Forward/ Back Propagation Network and Hyperparameter Tuning 5. Good Knowledge on Natural Knowledge Processing, Verbatim Analysis & Speech to Text / vice versa using few alternate approaches / techniques 6. Comfortable with statistical procedures, such as basic distributions, regressions, logistic models 7. Experience with advanced statistics and Machine Learning algorithms is a plus 8. Developing comprehensible analytical solutions to solve business problems using domain knowledge or 9. statistical procedures depending on the requirements of the project 10. Comfortable in representing the proceedings and/or findings in a power-point 11. Comfortable in mentoring junior resources, and creating an environment of learning in the team 12. Helping the company with Business Development initiatives such as sales collaterals, PoCs, Case Studies 13. Develop and define an area of expertise and take relevant trainings on the same for the organization 14. Contribute to org level activities, such as taking interviews 15. Work with team to estimate work effort 16. Understand the work methodology and be an active participant in strengthening the team 17. Liaising with coworkers and clients on several projects 18. Commitment to learning and continuous improvement 19. The candidate should be able to work under tight timelines with minimal supervision

Job Responsibilities: Substantial hands-on experience with data handling. Capable of managing large volumes of data, extract, clean and comprehend Experience with advanced statistics and Machine Learning algorithms like: Linear Regression, Logistic Regression, Tree-Based Models Experience with model deployment Experience with recommendation models, such as content-based filtering, collaborative filtering, and hybrid models. Knowledge of visualization tools such as POWER BI, Tableau is a plus. Hands on knowledge of end to end model development with code modularization. Hands on knowledge of SQL/PostgreSQL/Snowflake/DBT with understanding of CTEs, Joins, Window Functions, Aggregation Industry knowledge of Retail/E-commerce/Marketing is a plus. Developing comprehensible analytical solutions to solve business problems using domain knowledge or statistical procedures depending on the requirements of the project Comfortable in representing the proceedings and/or findings in a power-point Comfortable in mentoring junior resources, and creating an environment of learning in the team Helping the company with Business Development initiatives such as sales collaterals, PoCs, Case Studies Develop and define an area of expertise and take relevant trainings on the same for the organization The candidate should be able to work under tight timelines with minimal supervision Job Requirement EXPERTISE AND QUALIFICATIONS Experience: 4 to 7 Years Location: Bengaluru - Hybrid (HSR Layout Office) Must Have: • Statistics • Machine Learning • Python • SQL Good to Have: • PowerPoint & Excel