Data Scientist
GE Vernova · Posted Oct 23
Power generation, wind turbine, grid solution, and electrification services
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About the role
The Data Scientist executes end-to-end Data Science and Machine Learning workflows under guidance to deliver measurable value in industrial operations. The role focuses on data acquisition/cleaning, feature engineering, exploratory analysis, model development/validation, and contributes to deployment and monitoring in collaboration with data/platform engineering. Primary use cases include time-series forecasting, anomaly detection, and predictive maintenance, with Generative AI as an added advantage.
What you will do
- Execute DS/ML tasks across the model lifecycle: data acquisition, quality assessment/cleansing, feature engineering, and exploratory data analysis on industrial datasets (sensor/telemetry, logs, emissions, maintenance) with reproducible workflows.
- Train, tune, and validate models (regression, classification, and time-series methods such as ARIMA/Prophet; anomaly detection; ensembles). Document experiments and results clearly.
- Collaborate with data/platform engineering to contribute to data pipelines and model serving; support deployment activities and basic monitoring/drift checks under supervision.
- Produce clean, well-structured Python/SQL code; follow coding standards, version control, and experiment tracking practices.
- Create visual analyses and concise summaries to communicate findings and recommendations to teammates and stakeholders; incorporate feedback to iterate.
- Assist in measuring outcomes against success metrics (e.g., reliability, availability, efficiency, emissions, cost) and maintain project artifacts (reports, annotated code).
- Learn industrial context, data sources, and domain constraints; proactively identify data quality issues and propose fixes within established procedures.
- Participate in POCs/pilots, including GenAI/LLM-assisted analytics workflows (analytics automation, documentation) as an added advantage.
Skills used in this role
What the employer is looking for
- Education Qualification: Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with minimum 3 years of experience in Data Science/Machine Learning or closely related roles.
- Technical Expertise: Proficient in Python and SQL; hands-on with Pandas, NumPy, scikit-learn; basic exposure to TensorFlow/PyTorch is a plus.
- Applied experience with feature engineering, model selection, cross-validation, and performance measurement for time-series and classification/regression problems.
- Solid foundations in data management: ETL basics, data quality checks/cleansing, and working with large datasets.
- Familiarity with cloud ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI) and MLOps concepts (experiment tracking, model registry, monitoring) is a plus.
- Competent in visual analytics for EDA and communicating insights; experience with dashboards or notebooks preferred.
- Familiarity with big data/streaming technologies (e.g., Spark, Kafka) and real-time analytics considerations is a plus.
- Domain Knowledge: Exposure to industrial operations (Oil & Gas, Fossil Power, Renewable Power) is a plus; ability to learn failure modes, maintenance strategies, and process constraints and translate them into features and validation criteria.
- Basic understanding of business drivers and operational KPIs (availability, MTBF/MTTR, throughput, energy yield, emissions, cost) with the ability to connect analytical results to business value.
- Personal Attributes: Curiosity and continuous learning mindset; connects ideas and incorporates feedback quickly.
- Comfort in ambiguity at project/task level; states assumptions clearly and adapts based on new information.
- Clear communicator; explains technical information to teammates and stakeholders and asks clarifying questions to ensure shared understanding.
Benefits and support
- Relocation assistance
About GE Vernova
GE Vernova Inc. is a global energy company that provides equipment, services, and software to generate, transfer, orchestrate, convert, and store electricity. Operating through its Power, Wind, and Electrification segments, the company supports a broad customer base across more than 100 countries in powering economies and driving the energy transition. Formed as part of the strategic spin-off of General Electric's energy portfolio, GE Vernova is dedicated to electrifying and decarbonizing the world.
- Industry
- Energy
- Company size
- 75000+ employees
- Founded
- 2024
- Location
- Cambridge, Massachusetts, USA
- Funding stage
- Public Company
Leadership
Chief Executive Officer and President
Stephen F. Angel
Chairman of the Board
Lola Lin
Chief Legal Officer and Secretary
Roger Martella
Chief Corporate Officer, Chief Sustainability Officer & Head of Global Government Affairs
Eric Gray
CEO, Power Segment
Recent coverage
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