Lead Data Scientist

Overview

Lead AI/ML model development & validation for grid automation in energy sector

Key Responsibilities

• model validation
• automated testing
• data governance
• experiment design
• exploratory analysis
• stakeholder workshops

Tasks

-Establish clear validation frameworks to ensure models meet required performance standards and business objectives. -Collaborate with Application Architects, Data Engineers, ML Engineers and MLOps Engineers to improve data quality, enhance model performance, and ensure efficient deployment of validated models. -Responsible for exploratory data analysis (EDA), reporting and visualization of results. -Ensure data adheres to data governance policies and industry standards. -Lead project stakeholder workshops to shape scope, designs and outcomes to ensure project vision becomes reality. -Establish test procedures to validate models with real and simulated grid data. -Identify and address discrepancies between expected and actual model behavior, providing actionable insights to improve model performance. -Build necessary understanding and expertise to design and develop product features and applications such as Protection, Control, Monitoring and Communication -Implement automated testing strategies and pipelines to streamline model validation processes. -Communicate validation results, insights, and recommendations clearly to stakeholders, including product managers and leadership teams. -Design and conduct experiments to develop, test and validate AI/ML models in the context of energy systems and grid automation applications (including model selection, design, tuning, testing, refining, validation, optimization and deployment).

Requirements

• python
• tensorflow
• aws
• tableau
• phd
• 5 years

What You Bring

-Strong communication skills, with the ability to clearly explain complex validation results to non-technical stakeholders. -Experience in exploratory data analysis (EDA), delivering actionable insights from data and data storytelling. -Proficiency with data visualization tools and libraries such as Tableau, Power BI, or similar (matplotlib, bokeh, seaborn) to effectively present results and insights. -PhD, Master’s, or Bachelor’s degree in Data Science, Computer Science, Electrical Engineering, or a related field with hands-on experience in model development and validation. -Proven experience in the energy, smart infrastructure, or industrial automation sectors, with deep expertise in system protection, automation, monitoring, and diagnostics, typically acquired through a minimum of 5 years within a multinational manufacturing company. -Familiarity with data governance frameworks and validation standards in the energy sector. -Familiarity with big data tools and technologies, such as Hadoop, Kafka, and Spark. -Strong knowledge of statistical techniques, model technologies, performance metrics, and validation methodologies for AI/ML models. -Experience with data wrangling, feature engineering, and preparing datasets for model development. -Experience with cloud platforms (e.g., AWS, Azure, GCP) and deployment of models in cloud environments. -Knowledge of distributed computing environments and model deployment at scale. -Proficiency in programming languages such as Python, R, or MATLAB. -Substantial experience in building and validating AI/ML models, ensuring they meet business and technical requirements. -Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and model evaluation techniques.

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About Ge Vernova

-Traces roots back to Edison and Alstom, merging power, renewable, digital & financial wings. -Headquartered in Cambridge, MA, crafts large-scale gas turbines, SMRs, wind turbines, hydro and grid tech to fuel economies. -On the nuclear front, advancing small modular reactors (like BWRX‑300) in partnership with utilities and supporting semiconductor projects. -Wind prowess spans onshore, offshore and blade making—with key sites like Dogger Bank offshore and blade plants in Spain. -Electrification arm tackles grid stability: HVDC, transformers, storage, conversion, plus GridOS software powering smarter infrastructure. -Weaves finance and consulting through energy-infrastructure investments, funding solar farms to pipelines via GE Energy Financial Services.

Sector Specialisms