Data Scientist

Accurant International

9h•Remote

About The Position

We are hiring a Data Scientist to lead forecasting and optimization efforts within our platform. Reporting to the Sr. Director of Engineering, this role will define how quantitative models are built, productionized, and integrated into the system’s core functionality. Our DERMS creates and runs virtual power plants (VPPs), requiring forecasting and optimization of delivered capacity in real-world grid environments. This is a senior individual contributor role with broad ownership. You will design and deploy forecasting and optimization systems that directly shape product behavior and operational workflows. The role requires comfort working across the full stack of quantitative development — from raw data plumbing to production deployment. The candidate must have prior experience in electricity and capacity markets; must be knowledgeable in distribution grid topology; and operational boundaries of batteries, EVs, and large commercial buildings.

Requirements

7+ years of experience in data science, applied statistics, quantitative engineering, or related fields
Strong understanding of constraint programming and multi-objective optimization for real-time systems
Background in time-series analysis and regression-based modeling
Background in Bayesian modeling
Experience building optimization models in the electricity space and implementing them in the US energy / capacity markets
Proven experience deploying models into production environments
Comfort working with highly variable real-world data sets from numerous and varying sources and building supporting infrastructure
Strong programming skills in Python (or similar)
Ability to operate autonomously and make sound technical trade-offs
Strong communication skills across technical and non-technical audiences

Responsibilities

Design, build, and maintain forecasting and optimization models embedded in core product workflows
Model behaviors, impacts of weather, and behind the meter resources
Translate operational and business requirements into quantitative frameworks and production systems
Own the full lifecycle of quantitative systems — from data ingestion and feature development through deployment, monitoring, and reliability in production environments
Design and maintain data pipelines, schemas, and interfaces that support production forecasting and optimization workflows
Establish best practices for model development, validation, performance monitoring, and operational robustness
Partner closely with engineering to define interfaces, data contracts, and system boundaries that enable robust quantitative services
Provide technical leadership and guidance on quantitative methods across the organization