Lead Data Scientist

Core responsibilities:

• Collaborate directly with executive leadership to shape the technical AI strategy and product development at Arcadia
• Lead the development and integration of Gen-AI models and agents into Arcadia's products and processes
• Design and implement Machine Learning algorithms for critical energy applications, including forecasting, anomaly detection, and energy optimization
• Work with engineering to integrate models into the Arcadia Platform, contributing to design documents, code commits, and AI product documentation

This role creates positive change by developing AI solutions for the energy sector that help enterprises manage carbon emissions, reduce costs, and achieve sustainability goals, contributing to a clean energy future.

Required skills and qualifications:

• 2-5 years of experience developing Machine Learning/AI-based systems in an iterative or dynamic/agile development environment (energy sector experience preferred)
• Minimum 10-12 years of technical experience in data and/or engineering
• Master's or Doctoral degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields
• Fluency with Python or R, SQL, and Java or JavaScript
• Practical experience with Applied Machine Learning techniques including regression, classification, and supervised/unsupervised learning

Compensation and benefits:

• Target Base Range: $146,250 to $262,000 plus competitive benefits and equity component
• "Remote first" culture - work anywhere in the US with reliable internet
• Flexible PTO with no limit on vacation days for exempt employees
• 12 annual holidays, 10 days sick leave, up to 4 weeks bereavement leave
• 2 volunteer days off, 2 professional development days off
• 12 weeks paid parental leave for all parents
• 75-95% employer cost coverage for medical, dental, and vision benefits for employees and dependents

Arcadia is the global utility data and energy solutions platform that delivers solutions for every stage of the enterprise energy management lifecycle across carbon, cost, and reliability through its leading data platform and AI-powered analytics.