Data Scientist

SYSO Inc.; Boston (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

SYSO Inc. in Boston seeks a data scientist to build price forecasts and peak load models, leverage large energy datasets, and design market-ready optimization strategies for battery energy storage systems.

You will deploy predictive models, develop dashboards, and collaborate with Engineering, Operations, and Energy Markets teams to drive data-driven decisions. The role requires strong analytical and coding skills with Python, experience handling large, complex energy datasets, and a passion for

Qualifications

• BA/BS in Data Science, CS, or equivalent technical/mathematical field.
• Experience at any level from early-career to senior considered.
• Strong analytical and coding skills with proficiency in Python or other analytical tools.
• Ability to collaborate effectively across the company.
• Strong problem-solving and organizational skills.

Responsibilities

• Build price forecasts and peak load models using statistical and machine learning methods.
• Work with large datasets (price, generation, load, weather) across multiple ISO/RTO markets.
• Design and implement dispatch and optimization algorithms and market offer strategies for battery energy storage systems (BESS) to maximize economic performance while considering asset specifications, market constraints, and regulatory rules.
• Develop simulation environments to test the efficacy of various market participation strategies.
• Deploy and validate predictive models and workflows in production-grade code.
• Develop data visualizations and dashboards to summarize model outputs and market trends.
• Advise on the Company’s needs for developing new data science and analytical capabilities.
• Establish key performance metrics related to asset optimization.
• Collaborate closely with SYSO teams including Engineering, Operations, and Energy Markets teams to integrate data insights with real-time operations and market strategies.
• Conduct ad-hoc analyses to support business development and market strategies decisions.

Skills

Python

Analytical skills

Collaboration

Problem solving

Education

Bachelor's in Data Science or Computer Science

Master's or PhD in Data Science or CS

Tools

AWS

Metaflow

Databricks

Kubeflow

Job description

Key Responsibilities

• Build price forecasts and peak load models using statistical and machine learning methods.
• Work with large datasets (price, generation, load, weather) across multiple ISO/RTO markets.
• Design and implement dispatch and optimization algorithms and market offer strategies for battery energy storage systems (BESS) to maximize economic performance while considering asset specifications, market constraints, and regulatory rules.
• Develop simulation environments to test the efficacy of various market participation strategies.
• Deploy and validate predictive models and workflows in production-grade code.
• Develop data visualizations and dashboards to summarize model outputs and market trends.
• Advise on the Company’s needs for developing new data science and analytical capabilities.
• Establish key performance metrics related to asset optimization.
• Collaborate closely with SYSO teams including Engineering, Operations, and Energy Markets teams to integrate data insights with real-time operations and market strategies.
• Conduct ad-hoc analyses to support business development and market strategies decisions.

Required Qualifications/Skills/Education

• BA/BS in Data Science, Computer Science, or an equivalent technical or mathematical field.
• Relevant professional experience – candidates ranging from early-career to senior will be considered.
• Strong analytical and coding skills with proficiency in Python or other analytical tools.
• Ability to collaborate effectively and thrive working in a variety of capacities across the company.
• Strong problem-solving and organizational skills.

Desired Qualifications/Skills/Education

• Masters or PhD in Data Science, CS, or an equivalent technical or mathematical field.
• Familiarity with cloud computing ecosystems such as AWS, and data science frameworks such as Metaflow, Databricks or Kubeflow.
• Experience with statistical analysis and data visualizations using R.
• Experience formulating and solving mixed-integer linear programming (MILP) optimizations.
• Direct experience working in the energy industry.
• Demonstrated understanding of wholesale power market mechanics.
• Familiarity with renewable energy or battery storage development and operations.