Load Forecasting Data Scientist

ISO New England, Inc; Hartford (CT); Hybrid; USD 86,000 - 146,000; Full time

Benefits offered by this job

Competitive compensation with bonus

Tuition reimbursement

Wellness programs

Hybrid environment

Onsite dining options

Job summary

ISO New England, Inc. is seeking a forecasting-focused professional in Hartford, CT for a hybrid role.

You will lead and develop forecasting tools, engage in next-generation analytics, and collaborate across modeling, data management, software, and pipelines to support electricity demand planning. You’ll work on short- and long-term horizons, building data-driven methods and software, while communicating results to diverse audiences.

Qualifications

• Bachelor’s degree in a quantitative field.
• 3+ years of energy forecasting/data analytics experience.
• Proficiency in Python, R, MATLAB, or SAS.
• Experience with big data and probabilistic forecasting.

Responsibilities

• Drive forecasting, data management, and analytics work independently or in teams.
• Define requirements and workflows to support efficient solutions.
• Develop new forecasting methods, tools, and software.
• Communicate technical work through reports and presentations.
• Lead data pipelines, reusable software, and visualizations.
• Stay current with forecasting research and industry practices.

Skills

Forecasting

Data analytics

Communication

Big data

Geospatial analytics

Data wrangling

Team collaboration

Education

Bachelor’s degree in Economics/Math/Engineering/OR related field

Tools

Python

R

MATLAB

SAS

Job description

ISO New England, Inc offers a hybrid role in Hartford, CT where you can lead and develop forecasting tools that support electricity demand planning. You will work on next generation analytics and predictive modeling across short- and long-term time horizons, while collaborating with others on modeling, data management, software, and data pipelines. The role includes competitive pay, performance-based compensation, and benefits designed to support your growth and wellbeing.

What you’ll do

• Drive analytical, programming, modeling, and data management work independently and as part of a team.
• Define and document problem statements, project requirements, and related workflows to support efficient, effective solutions.
• Use a curious mindset and hands-on effort to improve existing processes and to create new forecasting methods, tools, and software.
• Share technical work clearly with diverse audiences through written reports and presentations.
• Focus on quality outcomes by leading development of data pipelines, reusable software packages, and visualizations.
• Stay current with forecasting research and industry best practices, evaluating and implementing relevant approaches strategically.

What you bring

• Bachelor’s degree in Economics, Mathematics, Engineering, Operations Research, or a related field.
• 3+ years of experience in the energy industry in forecasting, data analytics, or equivalent.
• Proficiency in at least one advanced programming language: Python, R, MATLAB, or SAS.
• Hands‑on experience developing software in a collaborative team environment.
• Experience working with big data, geospatial analytics, and/or probabilistic forecasting.
• Experience building applications that ingest and use data from multiple sources and formats, including data wrangling/data munging.
• Excellent written and verbal communication skills.

Tools you’ll use

• Python
• R
• MATLAB
• SAS

Benefits and work setup

• Competitive compensation with a base salary plus a performance bonus (USD 86,000 to 146,000 per year).
• Enhanced 401(k) and financial planning support.
• Tuition reimbursement and professional development opportunities.
• Wellness programs, including an onsite gym.
• Flexible work hours.
• Employee Business Networks.
• Onsite luncheon spaces with free coffee and a variety of dining options.
• Hybrid environment with 3 days/week onsite in Hartford, CT.
• Distance‑based relocation assistance available.

Nice to have (not required)

• Experience in electricity consumption modeling or economic modeling in the energy sector.
• Knowledge of distributed energy resources (such as photovoltaics and batteries), electric vehicles, and/or cold‑climate heat pumps.