Data Scientist

Schlumberger has an opening in Pune, India for a Data Science Lead role responsible for driving the successful delivery of AI solutions to internal customers. The role involves designing and executing predictive and analytical models on large-scale, complex datasets using statistical methods, traditional machine learning, and deep learning across domains such as computer vision and NLP. In addition, the candidate will lead the development of Generative AI solutions leveraging Large Language Models (LLMs) and Transformer architectures, including building RAG pipelines, agentic workflows, and multi-agent systems for autonomous reasoning and task execution. The role includes fine-tuning and evaluating foundation models, applying prompt engineering, and ensuring responsible AI practices. The individual will collaborate with cross-functional teams to integrate scalable AI solutions using MLOps/LLMOps, embeddings, and vector databases, while managing multiple projects, defining business problems, and delivering insights through presentations, prototypes, and stakeholder engagement. Key responsibilities Technology 8-10 years of hands on experience in design and development f state-of-the-art descriptive, diagnostic, predictive, and generative AI solutions aligned with business requirements Lead end-to-end delivery of multiple AI/ML projects (beyond PoC) including production-grade deployment and scaling Build and deploy enterprise-level solutions across traditional ML, deep learning (Computer Vision, NLP) and Generative AI (LLMs, Transformers, RAG, agentic systems) Architect secure, scalable, and reliable AI systems on cloud platforms, incorporating MLOps/LLMOps best practices Design solutions for high-dimensional, large-scale data, leveraging embeddings, vector databases, and hybrid retrieval techniques Drive deep technical understanding of models (both theoretical and practical), including fine-tuning, prompt engineering, and model evaluation Stay current with emerging tools, frameworks, and infrastructure, and rapidly build expertise in new technologies Proficiency in cloud platforms (GCP and Azure), with hands-on experience in building, deploying, and scaling secure AI/ML and GenAI solutions leveraging cloud-native services Business Engage with the business segments and internal stakeholders to capture requirements Work closely with analysts and business process managers to develop an end-to-end analytics solution Present and Communicate solution design with Business & IT audience Essential Qualifications Advanced (M.S/MTech/PhD) degree in Computer Science, Electrical Engineering, Mathematics and Computing, Operations Research from top tier institutes. Excellent communication, verbal, and written skills Key Competencies in data science technologies Strong theoretical foundations in machine learning, optimization, linear algebra, Probability & Statistics. Good understanding of Machine learning, Deep Learning Algorithms OR Optimization, Operations research, Decision Sciences algorithms Building and applying machine learning in real-world use cases Strong understanding, implementation and solution architecting of predictive / analytical modelling techniques, theories, principles, and practices Excellent knowledge of data mining / predictive modeling tools such as Python, TensorFlow, Keras, etc. Capable of delivering on multiple competing priorities with little supervision Experience/ exposure in deploying end to end AI Products on cloud Good To Have Skills And Abilities Track records of past publications & patents in the relevant topics is a plus Strong ability to work in a fast-paced environment Strong ability to work both autonomously and in a team Understanding of Oil and Gas domain is a plus Experience working with, processing and managing large data sets (multi-TB scale) is preferred Knowledge of designing distributed and parallelized algorithms for ML applications will be a plus Experience in real-time stream processing, IoT, Edge Analytics is a plus Keep continuously up to date on all assigned technologies Essential Qualifications Advanced (M.S/MTech/PhD) degree in Computer Science, Electrical Engineering, Mathematics and Computing, Operations Research from top tier institutes. Excellent communication, verbal, and written skills Key Competencies in data science technologies Strong theoretical foundations in machine learning, optimization, linear algebra, Probability & Statistics. Good understanding of Machine learning, Deep Learning Algorithms OR Optimization, Operations research, Decision Sciences algorithms Building and applying machine learning in real-world use cases Strong understanding, implementation and solution architecting of predictive / analytical modelling techniques, theories, principles, and practices Excellent knowledge of data mining / predictive modeling tools such as Python, TensorFlow, Keras, etc. Capable of delivering on multiple competing priorities with little supervision Experience/ exposure in deploying end to end AI Products on cloud Good To Have Skills And Abilities Track records of past publications & patents in the relevant topics is a plus Strong ability to work in a fast-paced environment Strong ability to work both autonomously and in a team Understanding of Oil and Gas domain is a plus Experience working with, processing and managing large data sets (multi-TB scale) is preferred Knowledge of designing distributed and parallelized algorithms for ML applications will be a plus Experience in real-time stream processing, IoT, Edge Analytics is a plus Keep continuously up to date on all assigned technologies SLB is an equal employment opportunity employer. Qualified applicants are considered without regard to race, color, religion, sex, national origin, age, disability, or other characteristics protected by law.