Principal Data Scientist
Principal Data Scientist Role
The Principal Data Scientist role will blend technical and operational projects and responsibilities to ensure Endurance Energy moves as quickly as possible. This role requires a data science background with strong fundamentals in engineering systems analysis, organizational skills, and technical proficiency; it also requires flexibility, creativity, and an open-minded attitude essential to an early-stage startup. In this role, you will own the end-to-end data lifecycle, from ingestion and modeling to visualization and strategic reporting. The Principal Data Scientist will be the primary technical lead responsible for identifying viable energy sites and running techno-economic analyses that drive strategic decisions and regulatory filings. As head of site selection, you will build and lead a multidisciplinary team spanning geoscience, techno-economic modeling, regulatory affairs, and customer development, owning the end-to-end process from initial resource screening through customer commitment and permitting.
Principal Data Scientist Responsibilities
Lead the Site Selection Team:
Develop and maintain advanced geospatial models to identify optimal sites for offshore energy development, integrating hydrothermal resource characterization with environmental constraints and regulatory boundaries.
Integrate datasets (bathymetry, seabed composition, marine traffic density, geohazards, projected LCOE, etc.) to rank sites based on feasibility.
Lead cross-functional coordination to bring Endurance Energy to market, working closely with Endurance Geologist(s), the Regulatory and Operations Lead, and Business Development Team to identify sites that satisfy technical feasibility, permitting timelines, and customer requirements. Build the bridge between scientific, engineering, regulatory, and commercial workstreams.
Work with Endurance’s geology and drilling engineering teams to identify specific drilling locations by collating topological and subsurface seismic survey data.
Build and maintain site-specific techno-economic models that quantify LCOE, CAPEX/OPEX sensitivities, and project IRR under varying resource quality and deployment scenarios.
Develop a deep understanding of the federal and state permitting landscape for offshore energy projects (BOEM, FERC, state coastal commissions) and incorporate permitting risk and timeline into site ranking frameworks.
Support customer engagement by producing site-specific analyses, resource summaries, and economic projections for prospective offtakers; translate technical findings into compelling narratives for hyperscaler and utility customers.
Coordinate with transmission planners and utilities to assess interconnection feasibility and cost for candidate sites; integrate grid access constraints into site selection criteria.
Co-lead expedition CONOPS:
Build predictive models for ocean current velocities and wave dynamics using time-series forecasting and physics-informed machine learning, applying systems engineering principles to complex fluid dynamics problems.
Analyze historical ocean data to project long-term trends and extreme weather events that impact asset integrity and inform autonomous system design requirements.
Validate models against real-time data to ensure accuracy for operational planning.
Configure data pipelines to analyze Endurance Energy’s system performance in nearly real-time, establishing intelligent sensor workflows and anomaly detection frameworks for subsea equipment.
Drilling & Operational Condition Reporting:
Design dynamic visualizations to communicate drilling conditions, weather windows, and operational risks for the engineering teams.
Lead Techno-Economic and Interconnection Analysis:
Perform Techno-Economic Assessments to model CAPEX/OPEX scenarios under various environmental conditions, leveraging optimization frameworks (e.g., CVXPY, CPLEX) for capacity expansion and production cost modeling.
Build data pipelines that analyze power flow and grid capacity and lead transmission interconnection requests, ensuring grid compatibility and estimating costs associated with transmission interconnection requests.
Develop Grid Connection and Customer Service Strategies
Evaluate grid connection pathways for each candidate site, analyzing transmission capacity, queue position strategies, and infrastructure upgrade requirements to minimize time-to-interconnection.
Model optimal delivery architectures (grid-connected, behind-the-meter, or hybrid configurations) to match customer load profiles, reliability requirements, and cost structures.
Develop frameworks to optimize site-customer pairing, considering proximity to load centers, transmission constraints, PPA pricing, and customer timeline requirements.
Analyze hyperscaler and data center load growth forecasts to identify high-priority service regions and inform proactive site development.
Required Skills
Advanced programming skills in Python/R; strong SQL. Strong background in applied statistics, model selection, tuning, and evaluation.
Direct experience working with geospatial datasets, experience with ArcGIS Pro (Model Builder) and ESRI Products, and Python/R geospatial packages such as geopandas, leaflet, PyShp, Rasterio.
Skilled in exploratory data analysis and handling imperfect real-world data.
4+ years of hands-on-experience in data analysis and quantitative modeling.
Experience with Git and the ability to write production code.
Nice-to-haves
Experience working with power market data and analytics, experience in modeling, forecasting, or optimizing within power/energy markets.
Experience building dashboards or internal tools using Quarto, Shiny, or Streamlit.
Demonstrated business transaction or sales experience.
Degree or background in engineering.