1452 Data Scientist Jobs - Page 34

The Senior AI Scientist is a technical role responsible for driving the design, development, and deployment of advanced AI components, models and systems. With 7+ years of experience in artificial intelligence and machine learning, this role is focused on hands-on research, solution prototyping, and enterprise-grade implementation across foundational models, generative AI, and multi-modal applications. The individual is expected to contribute deep technical expertise, execute on complex AI initiatives, and mentor junior scientists. The ideal candidate combines a strong research background with architectural thinking, practical implementation experience, and the ability to collaborate across cross-functional data, business, product and other teams. Responsibilities Develop the organizations AI research agenda, with a focus on AI (NLP/ML models), foundational models, generative AI, Agentic AI solutions and multi-modal systems aligned to business priorities. Develop end-to-end AI components and capabilities, from ideation and prototyping to scalable, enterprise-grade deployment. 3. Translate cutting-edge research into real-world AI components, performance optimization, data generation, and integration with existing data and platform ecosystems. Collaborate cross-functionally across product, business and other teams to drive alignment between AI research strategy and enterprise technology roadmaps. Ensure compliance and optimize performance, covering data governance, industry standards, and model efficiency. Ensure responsible and ethical AI development, incorporating model governance, explainability, fairness, and bias mitigation into the AI lifecycle. The person has to perform testing, validation of the components with reproducible matrix. The person has to perform cross collaboration and work on activities like generation of synthetic data, test suite development, Fine tuning and metrics validation. Good to have - Contribution to Whitepaper, blog authoring / contribution, Github Open source AI projects. Skills Expertise in software languages like Python / Java / .NET, R, PySpark, etc (Atleast 1 language) and SQL Expertise in developing AI and ML based solutions involving LLMs, NLP, Speech, Video, Agentic AI and other Deep Learning based models. Should have worked on Frameworks and libraries like Tensorflow, PyTorch, ScikitLearn, Ollama, Nemo, Transformers, Torch lightning, NIMS library, Unsloth, etc. Should have exposure working on Fine tuning of LLM models using Open source libraries. Ability to pursue new innovative solutions based on the new and latest technological developments and stacks. Ability to validate the solutions based on metrics, components to be part of larger integral system. Experience in Machine learning models like statistical, time series, stochastic, etc. Possess good concepts in various Machine learning algorithms and metrices. Experience in NLP based solutions like extraction, summarization, classification, etc using libraries like RASA, BERT, etc. Experience in developing chatbots, QA solutions, etc. Experience in replicating the solution for different business streams as per the requirement by fine tuning the models. Experience in using AI Cloud services in developing platform / end to end solutions. Good to have exposure to Cloud based deployment of AI solutions Exposure to atleast 1 Cloud services (AWS, Azure, GCP) is expected Should have experience in developing GenAI solutions making use of cache like RAGs (Chroma DB, FAISS, etc) and internal memory. Good to have experience in developing Hash, GraphAI, etc based NLP components like models, RAGs, etc Capable of communicating AI strategy, technical insights, and roadmaps to senior stakeholders for strategic alignment Solid grasp of data privacy, security, and compliance standards in WNS Adaptability and a continuous learning mindset and excellent communication

Grade / Level III Division / Department- Information Technology Job Purpose Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Develop custom data models and algorithms to apply to data sets. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes. Develop company A/B testing framework and test model quality. Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Lead the Analytics track for Project e-Parivartan which comprises of approx. 35 dashboards, 200 KPIs, 120 personas, Build up the 5 yrs Data Analytics track in consultation with relevant stakeholders with a vision of making the organization a Data Driven Organisation, Identify the use cases around AI/ ML Video Analytics and Natural language Processing on the CCTV footages for identification and automatic alerts for safety violation (Fire hazard, PPE .) Skills and academic qualifications Functional Skills Functional Skills Required - Strong problem solving skills with an emphasis on product development. Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. Knowledge of a variety of machine learning Technical Skills required - Min 12 Months Data Science Program; Project Management (PMP, PRINCE); Certifications in any of the below domains: Statistics and machine learning, coding languages C, C++, Java Script, Databases: R, Python, SLQ, etc.

Organization: At CommBank, we never lose sight of the role we play in other people’s financial wellbeing. Our focus is to help people and businesses move forward to progress. To make the right financial decisions and achieve their dreams, targets, and aspirations. Regardless of where you work within our organisation, your initiative, talent, ideas, and energy all contribute to the impact that we can make with our work. Together we can achieve great things. Job Title: Data Scientist Location: Bangalore Business & Team: Analytics BB Impact & contribution: As a Data Scientist, you will have the opportunity to apply your quantitative and computational skills within an applied and production-oriented R&D function within the group, focusing on cutting-edge deep learning and generative AI techniques. Your role will have a significant impact on our innovation capabilities and business processes by leveraging these advanced technologies Roles & Responsibilities: Model Development: Design and implement deep learning models, focusing on Generative AI applications like text generation, image synthesis, personalized recommendations, or autonomous decision-making. Fine-tune and adapt pre-trained models (e.g., GPT, DALL-E, Stable Diffusion) for specific tasks. Develop foundational components of multi-agent systems where agents use AI to collaborate or solve problems. Multi-Agent Integration: Build and test individual AI agents and integrate them into a multi-agent framework using libraries such as Ray, OpenAI API, or custom architectures. Design communication protocols between agents and their environment. End-to-End Deployment: Contribute to the deployment of at least one Generative AI model or a multi-agent application in production, ensuring scalability and performance. Collaboration and Research: Work closely with cross-functional teams to integrate Generative AI models into multi-agent solutions. Stay updated with advancements in Generative AI and multi-agent systems and experiment with cutting-edge technologies. Documentation: Maintain detailed documentation of experiments, models, and processes for reproducibility and team collaboration. Essential Skills: 5+ years of experience Proficiency with PyTorch, TensorFlow, or similar frameworks. Experience with LLM fine-tuning, prompt engineering, and model optimization. Familiarity with multi-agent frameworks like Ray, LangChain, or custom architectures. Working knowledge of distributed systems and cloud platforms (AWS, GCP, Azure). Education Qualifications: Bachelor’s degree in Engineering ( Computer Science/Information Technology). If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696. Advertising End Date: 18/06/2025 Show more Show less

As a Senior Data Scientist, you will apply your expertise in statistics, machine learning, and data analysis to extract valuable insights from structured and unstructured data. You will work closely with cross-functional teams to develop predictive models, improve business processes, and contribute to data-driven decision-making across the organization. Required Skills (Must have) Tech: Advanced programming knowledge in Python and SQL. Advanced knowledge in Probability and Statistics, including hypothesis testing. Advanced knowledge in Practical Machine Learning and awareness of the key-pitfalls in the practice of machine learning and approaches to addressing them. Advanced knowledge of data visualization technologies like Tableau, and PowerBI, and comfortable using relevant libraries in Python like seaborn and matplotlib. Experienced in modern development tools and writing code collaboratively. Intermediate knowledge of Cloud technologies and experience in developing data science solutions in one or more cloud platforms. Experienced in modern development tools, writing code collaboratively and developing solutions on cloud platforms. Non Tech : Ability to recognize and pursue pragmatic alternatives vis--vis a perfect solution, balancing priorities of time with potential business impact. Plan projects, break them down across individual data scientists in the team, track their performance and manage risks. Ability to storyboard an entire presentation to a non-technical audience. Ability to work independently to develop data science solutions, while also being able to work as part of a team to communicate findings and collaborate on solutions. Strong written skills. This is required for submitting technical papers, whitepapers, and developing project documentations. Technical leadership and mentorship to the community of data scientists in the organization. Required Skills (Good to have) Tech: Advanced knowledge in one or more areas besides Machine Learning – Operations Research, Natural Language Processing, Deep learning and its applications, Time Series forecasting at scale. Reinforcement Learning, Graph Machine Learning, Explainable Machine learning. Advanced understanding of Cloud technologies and experience of deploying applications on cloud. Non Tech: Ability to solution critical business problems into its component parts and match each such part with an appropriate technical approach. Roles and Responsibilities As Senior Data Scientist, you will be responsible for a wide range of engagements listed below: Formulates complex problems into hypotheses and proofs of concept for testing. Socializes this with the rest of the team and guides them to deliver on it. Applies business acumen in analyses to extract meaningful and actionable information. Communicates complex ideas and insights effectively to stakeholders with various levels of technical experience. Leverages various analytical techniques, appropriate to solving the business problem at hand. Performs research for solutions and solves problems efficiently to overcome data analytics challenges. Engages in the collection, integration, analysis, and presentation of data for various business contexts Understands good software development practices (versioning, peer reviews, refactoring, and pair programming), adapts them to the needs of the team and sets an example for others by following them. Creates and maintains technical documentation of the scientific experimentations performed, preferably in the CRISP-DM framework or like. Keeps up with the latest trends, technologies, and best practices in the field of Data Science and Engineering. Shares this knowledge with the rest of the data science team. Does peer reviews of codes and approaches of fellow members of the data science team. Provides mentorship to junior data scientists in the team. Looks for improvements in data science delivery processes, actively seeks buy-in on the improvements from peers and managers, implements them in the team and monitors their adoption. 4 to 6 years experience is mandatory

Job Type Full time Job Description Key Responsibilities: Analyze large datasets to extract actionable insights and drive data-driven decision-making. Develop predictive models and machine learning algorithms to solve business problems. Design and implement data preprocessing, feature engineering, and model training pipelines. Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions. Communicate findings and recommendations to stakeholders through data visualization and storytelling. Stay abreast of the latest developments in data science, machine learning, and AI technologies. Required Skills: 3-4 years of hands-on experience in data analysis and machine learning. Proficiency in programming languages such as Python or R for data manipulation and analysis. Experience with machine learning libraries/frameworks such as scikit-learn, TensorFlow, or PyTorch. Strong understanding of statistical concepts and techniques. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. Familiarity with SQL and relational databases for data querying and manipulation. Excellent problem-solving and analytical skills, with attention to detail. Good communication and collaboration skills, with the ability to work effectively in a team environment.

Senior Data Scientist Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus. Minimum 4 years of experience in Data Science and Machine Learning. In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models Utilize optimization tools and techniques, including MIP (Mixed Integer Programming. Deep knowledge of classical AIML (regression, classification, time series, clustering) Drive DevOps and MLOps practices, covering CI/CD and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. Kindly apply - https://careers.ey.com/job-invite/1606310/ and Vaishnavi - 9384017399 Contact - vaishnavi@gds.ey.com

Job Insights: 1. Develop and maintain AI models on time series & financial date for predictive modelling, including data collection, analysis, feature engineering, model development, evaluation, backtesting and monitoring. 2. Identify areas for model improvement through independent research and analysis, and develop recommendations for updates and enhancements. 3. Working with expert colleagues, Quant and business representatives to examine the results and keep models grounded in reality. 4. Documenting each step of the development and informing decision makers by presenting them options and results. 5. Ensure the integrity and security of data. 6. Provide support for production models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones. Qualifications: Bachelors or Masters degree in a numeric subject with understanding of economics and markets (eg.: Economics with a speciality in Econometrics, Finance, Computer Science, Applied Maths, Engineering, Physics) 2. Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning, Probability Theory and Linear Algebra. 3. Knowledge of Monte Carlo Simulations, Bayesian modelling & Causal Inference. 4. Experience with Machine Learning & Deep Learning concepts including data representations, neural network architectures, custom loss functions. 5. Proven track record of building AI models on time-series & financial data. 6. Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, PyMC, statsmodels). 7. Ability to write clear and concise code in python. 8. Intellectually curious and willing to learn challenging concepts daily.

Job Insights: 1. Develop and maintain AI models from inception to deployment, including data collection, analysis, feature engineering, model development, evaluation, and monitoring. 2. Identify areas for model improvement through independent research and analysis, and develop recommendations for updates and enhancements. 3. Working with expert colleagues and business representatives to examine the results and keep models grounded in reality. 4. Documenting each step of the development and informing decision makers by presenting them options and results. 5. Ensure the integrity and security of data. 6. Provide support for production models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones. Qualifications: 1. Bachelors / Master / PhD degree in Computer Science / Data Science / Mathematics / Statistics / relevant STEM field. 2. Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning, Probability Theory and Linear Algebra. 3. Experience with Machine Learning & Deep Learning concepts including data representations, neural network architectures, custom loss functions. 4. Proven track record of building AI model from scratch or finetuning on large models for Tabular or/and Textual data. 5. Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, transformers, langchain). 6. Ability to write clear and concise code in python. 7. Intellectually curious and willing to learn challenging concepts daily. 8. Knowledge of current Machine Learning/Artificial Intelligence literature. Notice period open

Role Title: Data Scientist Location: India Worker Type: Full-Time Employee (FTE) Years of Experience: 8+ years Start Date: Within 2 weeks Engagement Type: Full-time Salary Range: Flexible Remote/Onsite: Hybrid (India-based candidates) Job Overview: We are looking for an experienced Data Scientist to join our team and contribute to developing AIdriven data conversion tools. You will work closely with engineers and business stakeholders to build intelligent systems for data mapping, validation, and transformation. Required Skills and Experience: • Bachelor’s or Master’s in Data Science, Computer Science, AI, or a related field • Strong programming skills in Python and SQL • Experience with ML frameworks like TensorFlow or PyTorch • Solid understanding of AI-based data mapping, code generation, and validation • Familiarity with databases like SQL Server and MongoDB • Excellent collaboration, problem-solving, and communication skills • At least 8 years of relevant experience in Data Science • Open mindset with a willingness to experiment and learn from failures Preferred Qualifications: • Experience in the financial services domain • Certifications in Data Science or AI/ML • Background in data wrangling, ETL, or master data management • Exposure to DevOps tools like Jira, Confluence, BitBucket • Knowledge of cloud and AI/ML tools like Azure Synapse, Azure ML, Cognitive Services, and Databricks • Prior experience delivering AI solutions for data conversion or transformation Show more Show less

Data Analytics Engineer / Data Scientist Location- Mysuru (Preferred) or Remote (India) Full-Time | 3+ Years Experience ABOUT HOPTEKAI: At Hoptek, a Kearney Company, were building AI-powered SaaS products that help trucking companies operate smarter from pricing freight and planning networks to allocating assets and reducing waste. We’re looking for a Data Analytics Engineer / Data Scientist who’s excited to solve hard operations problems, build AI models that get embedded into our products, and help our customers get smarter through data. If you love building applied ML solutions and developing new ideas at the intersection of logistics and optimization, this role is for you. POSITION OVERVIEW: Build machine learning and optimization models to support pricing, routing, and network planning Partner with product and engineering teams to embed AI algorithms into customer-facing software Analyze freight networks and develop insights that drive operational efficiency Use PostgreSQL and Apache Superset to develop internal and customer-facing analytics as needed Prototype innovative solutions to unstructured problems using Python, OR techniques, and statistical methods Understand how customers interact with the platform and develop analytics to support adoption and value delivery What We’re Looking For: 3+ years of experience in data science, analytics engineering, or operations research Proficiency in Python, SQL, and relevant data/ML libraries (e.g., pandas, scikit-learn, XGBoost) Strong grasp of optimization techniques, network models, or decision science Familiarity with data visualization tools — especially Apache Superset Ability to work with real-world, messy logistics data and extract actionable intelligence Curiosity and creativity in approaching open-ended product and analytics challenges Bonus Points For: Experience in transportation, logistics, or freight planning Hands-on experience with graph analytics or geospatial data Experience productionizing ML/OR models within SaaS applications Exposure to pricing algorithms, dynamic optimization, or network simulations Why HOPTEKAI: Applied AI, Real Impact: Your work powers critical product decisions — from what to bid, to where to send the next truck Innovation-Driven: You’ll get to explore new techniques and shape the future of optimization in freight Close Loop from Data to Product: Help us transform ideas into algorithms, and algorithms into product features Mysuru Preferred: Collaborate on-site with our core team — or work remotely within India We’re Hiring Fast: Join a high-impact team at a critical growth moment

About the Company Resources is the backbone of Publicis Groupe, the world’s third-largest communications group. Formed in 1998 as a small team to service a few Publicis Groupe firms, Re:Sources has grown to 5,000+ people servicing a global network of prestigious advertising, public relations, media, healthcare, and digital marketing agencies. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury, and risk management to help Publicis Groupe agencies do their best: create and innovate for their clients. In addition to providing essential, everyday services to our agencies, Re:Sources develops and implements platforms, applications, and tools to enhance productivity, encourage collaboration, and enable professional and personal development. We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. With our support, Publicis Groupe agencies continue to create and deliver award-winning campaigns for their clients. About the Role The main purpose of this role is to advance the application of business intelligence, advanced data analytics, and machine learning for Marcel. The Data Scientist will work with other data scientists, engineers, and product owners to ensure the delivery of all commitments on time and in high quality. Responsibilities Design and develop advanced data science and machine learning algorithms, with a strong emphasis on Natural Language Processing (NLP) for personalized content, user understanding, and recommendation systems. Work on end-to-end LLM-driven features, including fine-tuning pre-trained models (e.g., BERT, GPT), prompt engineering, vector embeddings, and retrieval-augmented generation (RAG). Build robust models on diverse datasets to solve for semantic similarity, user intent detection, entity recognition, and content summarization/classification. Analyze user behaviour through data and derive actionable insights for platform feature improvements using experimentation (A/B testing, multivariate testing). Architect scalable solutions for deploying and monitoring language models within platform services, ensuring performance and interpretability. Collaborate cross-functionally with engineers, product managers, and designers to translate business needs into NLP/ML solutions. Regularly assess and maintain model accuracy and relevance through evaluation, retraining, and continuous improvement processes. Write clean, well-documented code in notebooks and scripts, following best practices for version control, testing, and deployment. Communicate findings and solutions effectively across stakeholders — from technical peers to executive leadership. Contribute to a culture of innovation and experimentation, continuously exploring new techniques in the rapidly evolving NLP/LLM space. Qualifications Minimum Experience (relevant): 3 years Maximum Experience (relevant): 5 years Required Skills Proficiency in Python and NLP frameworks: spaCy, NLTK, Hugging Face Transformers, OpenAI, LangChain. Strong understanding of LLMs, embedding techniques (e.g., SBERT, FAISS), RAG architecture, prompt engineering, and model evaluation. Experience in text classification, summarization, topic modeling, named entity recognition, and intent detection. Experience deploying ML models in production and working with orchestration tools such as Airflow, MLflow. Comfortable working in cloud environments (Azure preferred) and with tools such as Docker, Kubernetes (AKS), and Git. Strong experience working with data science/ML libraries in Python (SciPy, NumPy, TensorFlow, SciKit-Learn, etc.) Strong experience working in cloud development environments (especially Azure, ADF, PySpark, DataBricks, SQL) Experience building data science models for use on front end, user facing applications, such as recommendation models Experience with REST APIs, JSON, streaming datasets Understanding of Graph data, Neo4j is a plus Strong understanding of RDBMS data structure, Azure Tables, Blob, and other data sources Understanding of Jenkins, CI/CD processes using Git, for cloud configs and standard code repositories such as ADF configs and Databricks Preferred Skills Bachelor's degree in engineering, computer science, statistics, mathematics, information systems, or a related field from an accredited college or university; Master's degree from an accredited college or university is preferred. Or equivalent work experience. Advanced knowledge of data science techniques, and experience building, maintaining, and documenting models Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases preferably Graph DB. Experience building and optimizing ADF and PySpark based data pipelines, architectures and data sets on Graph and Azure Datalake. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. Strong analytic skills related to working with unstructured datasets. Build processes supporting data transformation, data structures, metadata, dependency and workload management. A successful history of manipulating, processing and extracting value from large disconnected datasets. Strong project management and organizational skills. Experience supporting and working with cross-functional teams in a dynamic environment. Show more Show less

Role: Data Scientist Experience: 2 - 5 Years Qualification: B.Tech /BE Location: Chennai Employment: Full-time Engage with clients to understand business problems and come up with approaches to solve them. Good communication skills, both verbal and written, to understand data needs and report results Create dashboards & Presentations to tell compelling stories about customers and their business Stay up to date with the latest technology, techniques, and methods in AI & ML An ideal candidate would have the below skill sets. Good understanding of statistical and data mining techniques. Hands-on Experience in building Machine Learning models in Python Ability to collect, clean, and engineer large amounts of data using SQL techniques. Data analysis and visualization skills in Power BI or Tableau to bring out insights from data Good understanding of GPTs/LLMs and its use in the field Experience working in at least one of the cloud platforms preferred: Azure, AWS, or GCP.

Client Name: WIPRO Location: PAN INDIA Mode: Hybrid Job Description: Experience Required: 10+ years in AI/ML and Solution Architecture roles (Strong programming and system integration background required) Key Responsibilities: Troubleshoot and fix an existing BERT-integrated Outsystems+AMP solution, including scheduler code debugging. Translate complex business requirements into scalable and integrative AI/GenAI solutions. Architect and guide end-to-end implementation of AI systems aligned with Ericssons target architecture (e.g., TAMP). Lead architectural reviews and support development teams to ensure solution compliance. Manage risks associated with AI models via standard risk assessment protocols. Create, maintain, and own architectural documentation and blueprints. Present technical concepts and designs to stakeholders. Collaborate with cross-functional teams including development and platform teams for successful project delivery. Additional Responsibilities: Apply advanced ML algorithms to solve business problems and drive value. Build and deploy data science solutions at scale (AWS Sagemaker, Kubernetes, Docker). Stay updated with current AI trends and contribute to applied research, innovation, and IP creation (e.g., publications, patents). Deliver insights to business leaders to influence decision-making. Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or related field. Proven track record in delivering AI/ML solutions (preferably in Finance domain). Recognized experience on data science platforms (e.g., Kaggle achievements is a plus). Strong coding background in Python and experience in cloud-native environments. Good to Have: Domain expertise in Finance. Contributions to open-source or research community (e.g., Kaggle, GitHub, papers).

Senior Data Scientist India - Pune At NICE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. So, what’s the role all about? We are seeking a highly skilled and experienced Senior Data Scientist to join our dynamic team. The ideal candidate should have a minimum 4s of years of experience in data science, with hands-on experience in developing and implementing Generative AI solutions. The Senior Data Scientist will be responsible for developing Machine Learning models and collaborating with cross-functional teams to solve complex business problems How will you make an impact? Develop and execute advanced analytics projects from end to end, including data collection, preprocessing, model development, evaluation, and deployment. Develop predictive models and machine learning algorithms to extract actionable insights from large and complex datasets. Utilize statistical techniques and quantitative analysis to identify trends, patterns, and correlations within the data. Collaborate with stakeholders to understand business requirements and translate them into analytical solutions that drive value and impact. Stay abreast of the latest advancements in Data Science, Machine Learning, Generative AI and recommend innovative approaches to solve business challenges Have you got what it takes? Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field; advanced degree (Master's or Ph.D.) preferred. Minimum of 4 years of hands-on experience in data science and machine learning , with at least 6 months of experience in Generative AI development. Proficiency in programming languages such as Python or R, as well as experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn, Hugging Face - Transformers, LangChain etc.). Strong understanding of machine learning techniques and algorithms, including supervised and unsupervised learning, regression, classification, clustering, and deep learning. Strong understanding of LLMs, NLP techniques, and evaluation methods for generative outputs. Solid foundation in prompt engineering for optimizing AI-generated outputs across different tasks and domains. Excellent problem-solving skills and ability to work independently as well as collaboratively in a fast-paced environment. Strong communication and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences. Proven leadership abilities, with experience in mentoring junior team members and leading cross-functional projects. Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects. Preferred Qualifications: Experience working in industries such as finance, banking. Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and related services for building and deploying machine learning models. Knowledge of data visualization tools (e.g., Tableau, Power BI) for creating interactive dashboards and reports. Publications or contributions to the data science community, such as conference presentations, research papers, or open-source projects. Hands-on experience with vector databases (e.g. Pinecone) and embedding techniques. What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr! Enjoy NICE-FLEX! At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 7409 Reporting into: Tech Manager Role Type: Individual Contributor

Company Description Primaspot AI is a new age startup transforming the field of Influencer Marketing through cutting edge algorithms for discovery of right influencers and state of the art agents for running campaigns across thousands of influencers across geographies at scale. We are helping big brands scale their marketing. Role Description This is a full-time on-site role for a Data Scientist completely remote. The company is headquartered in the USA. This role requires flexibility, as it will be a mix of data science and backend engineering work, where in the key work will be in areas related to core modelling, Gen AI and also deploying full scale backend architectures and working with databases. Qualifications Proficiency in Data Science and Data Analysis Experience in Building APIs Cloud exposure in work Git Strong skills in Statistics and Data Analytics Experience with Data Visualization tools and techniques Ability to communicate complex data findings in a clear and concise manner Excellent problem-solving and analytical thinking skills Experience with programming languages such as Python or R Bachelor’s degree in Data Science, Computer Science, Statistics or a related field Prior experience in the technology sector is a plus Requirements 2 + years experience Openness to work in dynamic environment Independent self learning working style Ability to cope with steep learning curve Benefits Completely remote Mentorship from industry leading experts from Matchmaking and Ecommerce domains CTC --> 8 - 10 lacs. ESOPs additional Fast career growth Show more Show less

Were looking for a skilled Generative AI Engineer to build and deploy AI-powered applications using OpenAI models and Azure Cloud services . The ideal candidate will have experience in Python , RAG architectures , and OCR integration . Key Responsibilities: Develop GenAI apps using OpenAI APIs (ChatGPT, GPT-4, Embeddings). Deploy and manage solutions on Azure (App Services, Azure Functions, Cognitive Services). Build RAG pipelines with vector databases (e.g., Azure Cognitive Search). Integrate OCR using tools like Azure Vision or Tesseract . Automate workflows using Python and Azure SDKs. Ensure performance, scalability, and security in production environments. Skills Required: OpenAI (ChatGPT, GPT-4, Embeddings) Azure Cloud (Azure OpenAI, Azure Functions, Cognitive Services) Python (LangChain, FastAPI, SDKs) RAG frameworks & vector databases OCR tools (Tesseract, Azure OCR) Docker, Git, CI/CD pipelines Preferred: Experience with LangChain or LLM orchestration Familiarity with Azure DevOps or GitHub Actions

Experience (guideline) 4+ years Responsibilities As a Data Scientist, you will develop the capability and application of business knowledge, mathematics, technology, design thinking and behavioural sciences to enable better decision support solutions within our data services and implement those decisions with the customer. This is your chance to flex your expertise in analysis, visualisation and algorithmic / mathematical computations and extract insights from data in response to these business problems, questioning and hypothesising using the data available from our customers, You will rapidly develop prototype applications that productionise the solutions identified so that they can deliver beta services to customers and work with other teams in order to transition these solutions into full service. You will enable the on-going creation, translation and consumption of data-driven insights to help customers make better decisions - increasing the efficiency and effectiveness of the services that we and our customers deliver. You will be dynamic and creative, and willing to take on any challenge and make a big impact. You will also demonstrate a strong entrepreneurial drive. Key Accountabilities Validate output from data analytics and balance this with knowledge and understanding to provide decision support to customers Assess and develop future capabilities and technologies relevant for big data and predictive analytics. You will be working with state of the art tools, assess future trends, and develop services as demonstrators and beta service offerings for use in the near future. Enable the on-going creation, translation and consumption of data-driven insights to help Rolls-Royce and our customers make better decisions - increasing the efficiency and effectiveness of the services that we and our customers deliver. Address business problems that are ill defined and shifting where factors affecting the problem are not completely understood. Contribute to the development or implementation of applications that demonstrate and illustrate the impact of data science on customer operations. Trial new approaches, new techniques, new technologies, and assess the impact of the latest technology trends. Demonstrating how data, algorithms, programming and visualisations can be employed to develop next generation data services. Be instrumental in setting up and defining the capabilities needed to utilise business knowledge, mathematics, technology, design thinking and knowledge of behavioural sciences in our next generation data services. Key Experience and Qualifications Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience. An ability to apply logical, analytical and innovative thinking on a range of technical problems, with a particular bias towards the application of existing analytical methods, the development of new methods and software engineering. Experience with predicative analytics, advanced analytics and machine learning algorithms are essential. Domain knowledge of one of the following; gas turbine engines, aircraft engineering, airline operations or aviation maintenance repair and overhaul is highly desirable Ability to interpret complex business requirements, translating them into analytical problems and delivering high value outputs. Experienced in the use of one or more current analytical / big data technologies such as Azure (Machine Learning, Stream Analytics, Data Factories etc.), R, Python (including relevant libraries), SAS, MATLAB, Spark, Hive, Hadoop, SQL, Tableau, Power BI, SPSS, JMP etc. Experienced in exploring and visualising data, being able to work with large data sets. Proactive, persistent and customer focused with a high level of self-motivation, initiative, and able to stand-alone. Skilled communicator, able to engage with colleagues, customers and stakeholders and an ability to influence and negotiate compromise between different groups. Work Experience Experience (guideline) 4+ years Responsibilities As a Data Scientist, you will develop the capability and application of business knowledge, mathematics, technology, design thinking and behavioural sciences to enable better decision support solutions within our data services and implement those decisions with the customer. This is your chance to flex your expertise in analysis, visualisation and algorithmic / mathematical computations and extract insights from data in response to these business problems, questioning and hypothesising using the data available from our customers, You will rapidly develop prototype applications that productionise the solutions identified so that they can deliver beta services to customers and work with other teams in order to transition these solutions into full service. You will enable the on-going creation, translation and consumption of data-driven insights to help customers make better decisions - increasing the efficiency and effectiveness of the services that we and our customers deliver. You will be dynamic and creative, and willing to take on any challenge and make a big impact. You will also demonstrate a strong entrepreneurial drive. Key Accountabilities Validate output from data analytics and balance this with knowledge and understanding to provide decision support to customers Assess and develop future capabilities and technologies relevant for big data and predictive analytics. You will be working with state of the art tools, assess future trends, and develop services as demonstrators and beta service offerings for use in the near future. Enable the on-going creation, translation and consumption of data-driven insights to help Rolls-Royce and our customers make better decisions - increasing the efficiency and effectiveness of the services that we and our customers deliver. Address business problems that are ill defined and shifting where factors affecting the problem are not completely understood. Contribute to the development or implementation of applications that demonstrate and illustrate the impact of data science on customer operations. Trial new approaches, new techniques, new technologies, and assess the impact of the latest technology trends. Demonstrating how data, algorithms, programming and visualisations can be employed to develop next generation data services. Be instrumental in setting up and defining the capabilities needed to utilise business knowledge, mathematics, technology, design thinking and knowledge of behavioural sciences in our next generation data services. Key Experience and Qualifications Degree level education in Mathematics, Scientific, Computing or Engineering discipline or equivalent experience. An ability to apply logical, analytical and innovative thinking on a range of technical problems, with a particular bias towards the application of existing analytical methods, the development of new methods and software engineering. Experience with predicative analytics, advanced analytics and machine learning algorithms are essential. Domain knowledge of one of the following; gas turbine engines, aircraft engineering, airline operations or aviation maintenance repair and overhaul is highly desirable Ability to interpret complex business requirements, translating them into analytical problems and delivering high value outputs. Experienced in the use of one or more current analytical / big data technologies such as Azure (Machine Learning, Stream Analytics, Data Factories etc.), R, Python (including relevant libraries), SAS, MATLAB, Spark, Hive, Hadoop, SQL, Tableau, Power BI, SPSS, JMP etc. Experienced in exploring and visualising data, being able to work with large data sets. Proactive, persistent and customer focused with a high level of self-motivation, initiative, and able to stand-alone. Skilled communicator, able to engage with colleagues, customers and stakeholders and an ability to influence and negotiate compromise between different groups.

Who We Are Simpplr is the AI-powered platform that unifies the digital workplace - bringing together engagement, enablement, and services to transform the employee experience. It streamlines communication, simplifies interactions, automates workflows, and elevates the everyday experience of work. The platform is intuitive, highly extensible, and built to integrate seamlessly with your existing technology. More than 1,000 leading organizations - including AAA, the NHS, Penske, and Moderna - trust Simpplr to foster a more aligned and productive workforce. Headquartered in Silicon Valley with global offices, Simpplr is backed by Norwest Ventures, Sapphire Ventures, Salesforce Ventures, and Tola Capital. Learn more at simpplr.com . About the Role Join our forward-thinking team as a Data Scientist where you will address real-world challenges through the lens of AI innovation, specifically focusing on Enterprise Search, Personalization, Content Recommendation, and pioneering work with custom LLM fine-tuning. Work in an environment that fosters collaboration among highly skilled professionals to build next- generation products that significantly impact our clients operational effectiveness. Key Responsibilities Innovate and develop scalable solutions leveraging AI technologies to process and analyze vast amounts of data efficiently. Quickly prototype, test, and deploy effective AI solutions, managing project timelines and deliverables while incorporating the latest advancements in AI research. Engage with cross-disciplinary teams to identify and implement AI-driven enhancements for user experiences, leading the charge from ideation to deployment. What We re Looking For 3-5 years of experience in crafting and implementing AI models, with a particular interest in applications within Enterprise Search and Content Personalization. Solid grounding in AI technologies, with proficiency in Python and familiarity with AI development frameworks. Interest or experience in ML-Ops, emphasizing the journey from concept to production scalability of ML models. Openness to candidates with a robust background in backend development who have delved into AI, especially those who have engaged in Enterprise Search, Developing learning to rank models, Agentic Workflows and LLM fine-tuning. Knowledge in developing analytical applications and working with cloud platforms, capable of managing large data sets and complex AI models. Technical skill sets Strong coding skills Understanding basics of Machine Learning, Deep Learning, and Natural Language Processing algorithms Experience in working with data annotation tools and building ML evaluation pipelines Comfort with working in multiple tech stacks Experience in API Development, Docker and AWS Services Nice to have: Experience in ML research, focusing on LLMs, Information Retrieval Systems, Reinforcement Learning, Knowledge Graphs, Agentic Workflows, Retrieval-Augmented Generation (RAG), Recommender Systems, Scaling, Monitoring, and Deploying LLMs Our Ideal Candidate We are in search of individuals who are not merely experienced but deeply passionate about unearthing new challenges and inquiries in the realm of AI. We value creativity, positivity, work ethic and the pursuit of answering intricate questions with methodical accuracy. Multiple positions at different seniority levels are available. Simpplr s Hub-Hybrid-Remote Model: At Simpplr we believe that when work is good, life is better and that belief guides all we do. Including how we approach our flexible work model. Simpplr operates with a Hub-Hybrid-Remote model. This model is role-based with exceptions and provides employees with the flexibility that many have told us they want. Hub - 100% work from Simpplr office. Role requires Simpplifier to be in the office full-time. Hybrid - Hybrid work from home and office. Role dictates the ability to work from home, plus benefit from in-person collaboration on a regular basis. Remote - 100% remote. Role can be done anywhere within your country of hire, as long as the requirements of the role are met.

Job Title Lead Data Scientist Job Description Job Description About Signify Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting. Through our leadership in connected lighting and the Internet of Things, we're breaking new ground in data analytics, AI, and smart solutions for homes, offices, cities, and beyond. At Signify, you can shape tomorrow by building on our incredible 125+ year legacy while working toward even bolder sustainability goals. Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers you to grow your skills and career. Join us, and together, we'll transform our industry, making a lasting difference for brighter lives and a better world. You light the way. More about the role we're looking for a Data Scientist to work on Deep learning, machine learning, data mining, and statistical modelingfor providing predictive and prescriptive enterprise analytics. Successful candidates will be expected to guide a team of Data Scientists, investigate state of the art techniques in advanced machine learning and statistical modeling, and design, develop, and deploy state-of-art, scalable systems for innovative analytics applications across various functional areas (eg Finance, Sales, Marketing, Supply Chain, etc). Applicants will be expected to work with a diverse set of data sources, such as time series data, graph data, semi-structured and unstructured data, and build statistical / machine-learning / Deep Learning/Gen AI models in support of on-demand, real-time analytic services. The applicant should also have strong skills in explaining the analytic models and outcomes to business stakeholders. you'll be part of the Signify s Enterprise Data & Analytics team, based in Bangalore. More about you Bachelors or Masters degree in Computer Science, Statistics, Mathematics, or a related field 4+ years of hands-on experience in data science or a related field with demonstrated history of delivering analytics models and solutions Strong programming skills in Python, PySpark or other statistical programming languages Strong foundation in machine learning and deep learning algorithms and expertise in natural language processing (NLP) and computer vision techniques Experience with popular deep learning frameworks such as TensorFlow and PyTorch Research and explore the latest advancements in generative AI, including techniques like natural language processing (NLP), computer vision, and machine learning Develop and implement generative AI models and algorithms to address specific business challenges Train and fine-tune generative AI models using large datasets and industry-specific knowledge to improve accuracy and efficiency Knowledge of cloud platforms like AWS, GCP, or Azure Strong problem-solving skills, communication skills and the ability to think creatively and strategically with a focus on business outco Everything we'll do for you Opportunity to work on some of the highly complex and challenging business problems across a variety of functional and business domains. Competitive salary depending on experience. Extensive set of tools to drive your career, such as a personalized learning platform, training and coaching

We are seeking a Data Scientist Engineer with experience bringing highly scalable enterprise SaaS applications to market. This is a uniquely impactful opportunity to help drive our business forward and directly contribute to long-term growth at Virtana. If you thrive in a fast-paced environment, take initiative, embrace proactivity and collaboration, and you're seeking an environment for continuous learning and improvement, we d love to hear from you! Virtana is a remote first work environment so you'll be able to work from the comfort of your home while collaborating with teammates on a variety of connectivity tools and technologies. Role Responsibilities: Research and test machine learning approaches for analyzing large-scale distributed computing applications. Implement different models AI and ML algorithms for prototype and production systems. Test and refine the models and algorithms with live customer data to improve accuracy and efficacy. Work with other functional teams to integrate implemented systems into the SaaS platform Suggest innovative and creative concepts and ideas that would improve the overall platform Qualifications: The ideal candidate must have the following qualifications: 3+ years experience in practical implementation and deployment of ML based systems preferred. BS/B Tech or M Tech/ MS (preferred) in Applied Mathematics or Statistics, or CS/Engineering with strong mathematical/statistical background Strong quantitative and analytical skills, especially statistical and ML techniques, including familiarity with different supervised and unsupervised learning algorithms Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization Experience in working on modeling graph structures related to spatiotemporal systems Programming skills in Python Experience in developing and deploying on cloud (AWS or Google or Azure) Experience in understanding and usage of LLM models and Prompt engineering is preferred. Good verbal and written communication skills Familiarity with we'll-known ML frameworks such as Pandas, Keras and TensorFlow

We are seeking a Senior Data Scientist Engineer with experience bringing highly scalable enterprise SaaS applications to market. This is a uniquely impactful opportunity to help drive our business forward and directly contribute to long-term growth at Virtana. If you thrive in a fast-paced environment, take initiative, embrace proactivity and collaboration, and you're seeking an environment for continuous learning and improvement, we d love to hear from you! Virtana is a remote first work environment so you'll be able to work from the comfort of your home while collaborating with teammates on a variety of connectivity tools and technologies. Role Responsibilities: Research and test machine learning approaches for analyzing large-scale distributed computing applications. Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy, efficacy, and robustness Work closely with other functional teams to integrate implemented systems into the SaaS platform Suggest innovative and creative concepts and ideas that would improve the overall platform. Qualifications: 6 + years experience in practical implementation and deployment of large customer-facing ML based systems. MS or M Tech (preferred) in applied mathematics/statistics; CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization Experience in working on modeling graph structures related to spatiotemporal systems Programming skills in Python is a must Experience in understanding and usage of LLM models and Prompt engineering is preferred. Experience in developing and deploying on cloud (AWS or Google or Azure) Good verbal and written communication skills Familiarity with we'll-known ML frameworks such as Pandas, Keras, TensorFlow

we're looking for a Principal Data Scientist to work on GenAI & machine learning for providing predictive and prescriptive enterprise analytics. Successful candidates will be expected to guide a team of Data Scientists, investigate state of the art techniques in GenAI, LLM fine tunning, advanced machine learning and statistical modeling, and design, develop, and deploy state-of-art, scalable systems for innovative analytics applications across various functional areas (eg Finance, Sales, Marketing, Supply Chain, etc). Applicants will be expected to work with a diverse set of data sources, such as time series data, graph data, semi-structured and unstructured data, and build statistical/machine-learning models in support of on-demand, real-time analytic services. The applicant should also have strong skills GenAI solution development and implementation, should be aware of latest tools and technology in the area of GenAI, Agentic AI, and should be a power user of at least one of GenAI tool (ChatGPT, Copilot etc). The candidate should be proficient in explaining the analytic models and outcomes to business stakeholders. What you'll do Lead, guide and advice a team of Data Scientists and manage project timelines, resources, and deliverables Conceptualize, develop and implement GenAI/Agentic AI solutions at an enterprise level. Focus on productization & scalability of GenAI/ML solutions that can be replicated across multiple markets / businesses to solve similar business problems. Work with business groups to ensure models can be implemented as part of a delivered solution and can be replicated across multiple markets / countries Keep abreast of the latest developments in the field of GenAI, Agentic AI, ML, data science, by continuous learning and proactively champion promising new methods relevant to the problems at hand Develop and implement statistical models, machine learning algorithms, and other advanced analytics techniques to solve complex business problems Conduct data analysis, data mining, and data visualization to identify patterns and insights in large datasets Collaborate with cross-functional teams to develop and implement data-driven solutions that improve business performance Present findings and recommendations to senior leadership and stakeholders in a clear and concise manner Stay up-to-date with the latest trends and advancements in data science, machine learning, and artificial intelligence Be overall responsible for all the Data Science related deliverables and in meeting accuracy targets Research, design and prototype robust and scalable models based on machine learning, data mining, and statistical modeling to answer key business problems Present findings to stakeholders to drive improvements and solutions from concept through to delivery What you'll need Working knowledge in GenAI, Agentic AI solution development and implementation, finetuning open source LLM s and contextualizing the same with internal enterprise data. Working knowledge with at least one of the GenAI tool (ChatGPT, Copilot etc) PhD / Masters / B.Tech in computer science, computer engineering with 12+ years of demonstrated experience in the Advanced Analytics / Machine Learning field Strong programming skills in languages such as Python, and SQL and various open source machine learning and analytics packages Demonstrated history of driving and delivering analytics models and solutions Deep knowledge of fundamentals of machine learning, data mining and statistical modeling, and extensive experience applying these methods to real world problems Hands on working experience on at least one of the MLOps Platform like AWS Sagemaker, Dataiku, Data Robot Experience with big data technologies such as Hadoop, Spark, and NoSQL databases Excellent communication and interpersonal skills, with the ability to work effectively in a team environment Strong problem-solving skills and the ability to think creatively and strategically. Ability and inclination to work in multi-disciplinary environments, and desire to see ideas realize in Practice. What you'll get in return Opportunity to work on some of the highly complex and challenging business problems across a variety of functional domains and consumer markets. Competitive salary depending on experience. Extensive set of tools to drive your career, such as a personalized learning platform, free training and Coaching

As a part of our dynamic team, you'll have the opportunity to collaborate with top healthcare providers in the country, applying AI-powe'red RPM solutions to tackle some of the most pressing challenges in healthcare - enhancing staff efficiency, improving patient outcomes, and pioneering the next generation of care models. Responsibilities To initiate, develop and optimize algorithms to solve healthcare problems To ensure a constant flow of case studies/publications from acquired health datasets To extract feedback for product and marketing in order to improve and optimize their functions To optimize and upgrade existing pipelines and processesTo ensure performance on par with business requirements To keep the software stack and implementation up to date with the latest advancements in the industry Requirement 5+ years of relevant work experienceStrong fundamentals in statistics and machine learning Excellent scripting and programming skills with Python(preferred), Julia or R Experience of working with Time series data Experience of mining, handling and analyzing big datasets Experience of working with TensorFlow/Keras/Pytorch Experience of working with Spark/Hadoop and help setup pipelines Excellent data communication, sharp analytical abilities with proven design skills along with ability to think critically of the current system and existing projects

We're looking for a passionate Senior Data Scientist - Generative AI who thrives at the intersection of AI research & real-world applications. This role is ideal for someone who s eager to build, experiment & scale LLM-powe'red solutions in enterprise environments. This role blends hands-on Problem solving, Research, Engineering & collaboration across multidisciplinary team driving innovation across industries/ domains . Job Description: Design and implement advanced GenAI solutions using LLMs, Transformers & Prompt engineering Own the full lifecycle: from problem scoping & model design to deployment & post-production optimization Build & maintain reusable frameworks, pipelines, & prompt libraries Participate in code reviews & contribute to maintaining high code quality standards Conduct research & experimentation to evaluate new techniques in GenAI & NLP space Present insights & recommendations to clients & internal stakeholders through compelling storytelling & visualizations Mentor junior team members & contribute to knowledge-sharing initiatives Must Have Skills: 5-10 years of experience in Data Science - NLP, with at least 2 years in GenAI/LLMs Proficiency in Python, SQL & ML frameworks (eg, PyTorch, TensorFlow, Hugging Face) Hands-on experience with GenAI tools like LangChain, LlamaIndex, RAG pipelines, Prompt Engineering & vector databases (eg, FAISS, ChromaDB) Strong understanding of NLP techniques including embeddings, topic modeling, text classification, semantic search, summarization, Q&A, chatbots, etc Experience with cloud platforms (GCP, AWS, or Azure) and CI/CD pipelines Experience integrating LLMs via Azure OpenAI, Google Vertex AI or AWS Bedrock Ability to work independently & drive projects end-to-end from development to production Strong problem-solving, data storytelling & communication skills Preferred Skills: Experience in domains like BFSI, Retail, CPG, FMCG, Healthcare, etc Exposure to MLOps tools like MLflow, Kubeflow, or Vertex AI Publications or contributions to open-source GenAI projects

Its fun to work in a company where people truly BELIEVE in what they are doing! Were committed to bringing passion and customer focus to the business. Senior Data Scientist - Generative AI Role Overview: We re looking for a passionate Senior Data Scientist - Generative AI who thrives at the intersection of AI research & real-world applications. This role is ideal for someone who s eager to build, experiment & scale LLM-powered solutions in enterprise environments. This role blends hands-on Problem solving, Research, Engineering & collaboration across multidisciplinary team driving innovation across industries/ domains . Job Description: Design and implement advanced GenAI solutions using LLMs, Transformers & Prompt engineering Own the full lifecycle: from problem scoping & model design to deployment & post-production optimization Build & maintain reusable frameworks, pipelines, & prompt libraries Participate in code reviews & contribute to maintaining high code quality standards Conduct research & experimentation to evaluate new techniques in GenAI & NLP space Present insights & recommendations to clients & internal stakeholders through compelling storytelling & visualizations Mentor junior team members & contribute to knowledge-sharing initiatives Must Have Skills: 5-10 years of experience in Data Science - NLP, with at least 2 years in GenAI/LLMs Proficiency in Python, SQL & ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) Hands-on experience with GenAI tools like LangChain, LlamaIndex, RAG pipelines, Prompt Engineering & vector databases (e.g., FAISS, ChromaDB) Strong understanding of NLP techniques including embeddings, topic modeling, text classification, semantic search, summarization, Q&A, chatbots, etc Experience with cloud platforms (GCP, AWS, or Azure) and CI/CD pipelines Experience integrating LLMs via Azure OpenAI, Google Vertex AI or AWS Bedrock Ability to work independently & drive projects end-to-end from development to production Strong problem-solving, data storytelling & communication skills Preferred Skills: Experience in domains like BFSI, Retail, CPG, FMCG, Healthcare, etc Exposure to MLOps tools like MLflow, Kubeflow, or Vertex AI Publications or contributions to open-source GenAI projects Location : All Fractal Locations - Mumbai, Bengaluru, Gurugram, Pune, Noida, Chennai, Pune, Coimbatore, Hyderabad Ready to Build the Future of AI? If youre passionate about building generative AI solutions that scale, wed love to hear from you. Bring your innovation, drive, and curiosity to Fractal where AI meets real impact . If you like wild growth and working with happy, enthusiastic over-achievers, youll enjoy your career with us! Not the right fit? Let us know youre interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!