Sr Data Scientist - Carbon Management Platforms job opportunity at GE Vernova.

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DateMore Than 30 Days Ago bot
GE Vernova Sr Data Scientist - Carbon Management Platforms
Experience: General
Pattern: full-time
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loacation Bengaluru, India
loacation Bengaluru....India

Job Description Summary The Sr. Data Scientist will work in cross-functional teams to design, develop, and deploy advanced analytics solutions across the Energy domain — including power generation, oil & gas, and industrial manufacturing. You will apply statistical modeling, machine learning, optimization, forecasting, anomaly detection, and NLP techniques to solve high-value business problems at scale. In addition, you will have the opportunity to explore and apply modern Generative AI approaches (LLMs, Retrieval-Augmented Generation, and agent-based orchestration) where appropriate to accelerate insights and productivity — with a balanced focus on both research thinking and production delivery. Job Description As a Sr. Data Scientist, you will be part of cross-disciplinary team on commercially facing development projects, typically involving large, complex datasets. These teams include data scientists, software engineers, product managers, domain specialists, and end users — working together to deliver measurable business value. Typical application areas include remote monitoring solutions on carbon management, carbon reduction solutions based on operations optimization, predictive maintenance, financial & operational risk modeling, intelligent decision support etc., In this role, you will: Develop scalable analytics and machine learning solutions to address optimization, forecasting, anomaly detection, and NLP needs. Translate concepts and analytical approaches into commercially viable products and services in collaboration with software developers and engineers. Design and conduct exploratory and targeted analyses to understand data behavior and uncover actionable insights. Contribute to model lifecycle activities including feature engineering, model training, validation, deployment, and monitoring (MLOps). Work closely with data engineers on data quality assessment, data preparation, and data pipelines. Document your work clearly (reports, notebooks, annotated code) and communicate findings to technical and non-technical stakeholders. Mentor junior team members and support best-practice adoption across the team. Engage with customers to understand requirements, present results, and shape solution direction. (Advantage) Explore and prototype modern Generative AI capabilities such as: LLM-powered applications Retrieval-Augmented Generation (RAG) Multi-agent orchestration for automation — with attention to safety, reliability, and business value. Education Qualification Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with advanced experience. Desired Characteristics Strong proficiency in at least one analytics or programming language (e.g., Python). Demonstrated experience in data cleansing, data quality assessment, and analytical data preparation. Hands-on experience applying descriptive statistics, feature engineering, and predictive modeling to real-world/industrial datasets. Ability to present insights clearly through visualizations and compelling storytelling. Technical Expertise Experience with Python, PyTorch or TensorFlow, and ML lifecycle tools such as MLflow. Awareness of data management and data engineering best practices. Awareness of real-time or near-real-time analytics deployment patterns. Working knowledge of cloud concepts (AWS basics preferred) for service deployment. Exposure to GenAI / LLM concepts (RAG, LLM apps, multi-agent orchestration) — nice to have, not mandatory . Domain Knowledge Awareness of industry and technology trends in Power Generation, Oil & Gas, or Manufacturing. Understanding of customer value drivers, performance metrics, and stakeholder needs in industrial contexts. Leadership Proven ability to function effectively within collaborative, cross-disciplinary teams. Demonstrated problem-solving capability and critical thinking. Ability to influence through data, communicate trade-offs, and help guide decisions. Experience mentoring junior team members. Personal Attributes Comfortable operating in ambiguous environments and iterating toward clarity. Balanced mindset between research exploration and production-grade delivery . Willingness to travel occasionally when business needs require (advantage). Additional Information Relocation Assistance Provided: Yes

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