Senior Data Science Engineer
About The Position
As a Senior Data Science Engineer at REsurety, you’ll be a technical leader responsible for the architecture, maintenance, and rigorous validation of the models and tools that power REsurety’s core business. At the Senior level, you are a driven engineer and a creative problem solver. You will lead the development of sophisticated software that characterizes risk and accelerates the global development of clean energy, serving as a bridge between research, power markets, and production-grade engineering. This is a senior individual contributor role focused on technical leadership, system design, and cross-functional influence, not people management.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
- 5+ years of professional experience designing and operating data-intensive software systems in production environments.
- Expert-level proficiency in Python (including Pandas/NumPy) and SQL.
- Significant experience with time-series modeling, forecasting, machine learning, and statistical techniques in applied settings (e.g., Statsmodels, Scikit-learn, TensorFlow, or PyTorch).
- Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), including containerized workloads (Docker/ECS) and Infrastructure-as-Code (e.g., Terraform).
- Proven ability to lead technical initiatives across teams, making architectural decisions that balance correctness, performance, and maintainability.
Nice To Haves
- Domain expertise in clean energy, power markets, or energy analytics; experience in finance, offtake structures, or hedging is a strong plus.
- Experience building or supporting power flow or least-cost optimization models.
- Prior experience operating at a Senior level, leading cross-functional technical strategy and initiatives.
Responsibilities
- Own the end-to-end design and implementation of large-scale data and modeling applications, from ingestion and storage through modeling, validation, and production deployment.
- Implement modular, testable, and performant systems at scale, setting standards for code quality, security, and reliability across the organization.
- Contribute to schema and data-model design in Snowflake and Postgres to support massive, evolving meteorological and power market datasets.
- Establish and advocate for best practices in automated testing (unit, integration, data validation) for analytical and modeling workflows.
- Drive the development and evolution of time-series forecasting models in Python for energy prices, emissions, and load.
- Lead the evaluation, validation, and integration of new and complex data sources into production modeling systems.
- Partner with research, power markets, product, and engineering to translate exploratory analyses into robust, production-ready systems.
- Conduct deep-dive analyses into complex datasets (e.g., transmission constraints, solar irradiance, weather-driven dynamics) to surface market insights and modeling improvements.
- Provide technical mentorship and design guidance to mid-level engineers, raising the overall quality bar without direct people management.
- Act as a Subject Matter Expert (SME) for clean energy project characterization and power market dynamics.
- Clearly communicate complex technical concepts, assumptions, and validation results to internal stakeholders and external customers.
Benefits
- Benefits information can be found on our Careers page: https://resurety.com/about/careers/
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
1-10 employees
