Senior Data Science Engineer

Resurety Open Roles•Boston, MA

17h•Hybrid

About The Position

Are you looking for an engaging career in the clean energy markets? Do you want to work with a team of smart, passionate people changing the future of energy both financially and environmentally? Is Data Science your passion? If so, let’s connect! 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.