Power Markets Data Scientist & Optimization Analyst - Hybrid Remote

Pay Grade: M08

POSITION SUMMARY

The Power Markets Data Scientist & Optimization Analyst develops advanced analytical models, forecasting solutions, optimization frameworks, and decision-support tools that support Hoosier Energy's participation in RTO energy, capacity, transmission, congestion management, and ancillary services markets. The position combines power market expertise with modern data science techniques to improve market strategies, forecast market outcomes, optimize portfolio performance, and support enterprise decision-making.

This role serves as the lead analytical resource within the Power Markets group and works collaboratively with Information Technology (IT), Information Services (IS), System Operations, Strategic Planning, Finance, and Generation personnel to develop and enhance data solutions, reporting platforms, forecasting models, and analytical capabilities. The position transforms large volumes of market, operational, generation, transmission, weather, fuel, and financial data into actionable insights and visualizations that support both operational and strategic objectives.

The position supports market optimization, resource adequacy planning, congestion analysis, generation and load strategies, settlement validation, risk management, and long-term planning through the application of operations research, statistics, machine learning, and business intelligence techniques.

DUTIES AND RESPONSIBILITIES

• Develop, maintain, and enhance statistical, forecasting, optimization, and machine learning models supporting power market decision-making.
• Maintain and make recommendations to improve Hoosier Energy’s short-term hourly load forecast models.
• Perform analyses of load forecasts, energy market prices, congestion, losses, fuel costs, generation dispatch, transmission constraints, and resource adequacy requirements.
• Evaluate generation profitability, load-serving costs, market performance, and portfolio risk exposures through quantitative analysis.
• Conduct scenario analyses, sensitivity studies, and probabilistic forecasting to support strategic and operational decisions.
• Develop predictive and prescriptive analytics solutions that improve market performance, portfolio value, and asset utilization.
• Perform after-the-fact analysis of forecasting accuracy, bidding effectiveness, and market outcomes to drive continuous improvement.
• Develop optimization models supporting generation dispatch, energy portfolio management, resource adequacy planning, transmission utilization, congestion mitigation, fuel procurement, and energy storage operations.
• Apply operations research methodologies, mathematical programming, simulation techniques, and machine learning algorithms to improve market participation and portfolio value.
• Quantify risk and uncertainty associated with market prices, load forecasts, generation availability, transmission congestion, weather events, and regulatory changes.
• Support the evaluation of emerging technologies, market opportunities, and long-term resource planning alternatives through advanced modeling and scenario analysis.
• Analyze Financial Transmission Rights (FTRs), congestion exposure, and transmission-related market opportunities and risks.
• Partner with IT/IS personnel to define, develop, and enhance data pipelines, data integration processes, and analytical environments supporting power market analytics.
• Collaborate with technology teams to improve the availability, quality, structure, and governance of market, operational, financial, transmission, fuel, and settlement data.
• Develop analytical datasets, automated workflows, reusable models, and reporting tools that improve efficiency and analytical effectiveness.
• Support the design and implementation of cloud-based analytics, reporting, and business intelligence solutions in partnership with IT/IS teams.
• Develop and maintain dashboards, scorecards, visualizations, and decision-support tools utilizing software such as SAS, Power BI, Microsoft Fabric, Azure data services, or similar technologies.
• Promote data quality, reproducibility, documentation standards, and analytics best practices across Power Markets processes.
• Assist with the development and evaluation of generation offer strategies and load bidding strategies within MISO markets.
• Support validation of market settlements, MISO invoices, congestion charges, and transaction records.
• Maintain familiarity with corporate processes and systems impacted by MISO market operations, including load forecasting, scheduling, settlements, generation dispatch, and resource adequacy requirements.
• Provide analytical support during critical market events and operational decision-making periods.
• Collaborate with System Control, Generation, Portfolio, Forecasting, Finance, and Economic Development personnel to support analytical requirements and business initiatives.
• Communicate analytical findings and recommendations to both technical and executive audiences.
• Prepare reports, presentations, dashboards, and executive briefings supporting strategic and operational decision-making.
• Represent Hoosier Energy on MISO, ACES, and other industry working groups, committees, or task forces as assigned.
• Monitor industry developments, market design changes, and regulatory initiatives and assess potential impacts on Hoosier Energy's operations and strategy.

JOB SPECIFICATIONS

Education:

• Bachelor’s Degree in Operations Research, Data Science, Engineering, Mathematics, Statistics, Economics, Finance, Computer Science, Information Systems, Analytics or Related quantitative field minimum
• Graduate degree in a quantitative discipline preferred

Experience:

• 3 – 10 years of progressively responsible experience in power markets, energy analytics, operations research, data science, forecasting, business intelligence, engineering, quantitative analysis, finance, or a related field.
• 3 – 10 years’ experience applying statistical methods, optimization techniques, forecasting methodologies, and machine learning to solve complex business problems. Experience developing analytical models, dashboards, reporting solutions, and decision-support tools. Experience working with large datasets, databases, and data management processes.
• 3 – 10 years’ experience in wholesale electric markets, utility operations, generation planning, transmission planning, or energy portfolio management is preferred.

Skills and Abilities:

Technical Competencies

• Statistical analysis and predictive modeling
• Time-series forecasting
• Machine learning and artificial intelligence applications
• Operations research and optimization techniques
• Simulation and scenario analysis
• Database management and SQL
• Data visualization and business intelligence
• Power BI, Microsoft Fabric, Azure Data Services, or similar analytics platforms
• Data engineering principles and data governance practices
• Familiar with ETL software

Professional Skills

• Strong analytical and critical thinking skills
• Excellent written and verbal communication skills
• Ability to communicate effectively with both technical and non-technical audiences
• Strong problem-solving and decision-making capabilities
• Ability to manage multiple assignments and priorities
• Ability to work collaboratively across departments
• Demonstrated initiative and continuous improvement mindset
• Ability to adapt to evolving market conditions and business needs

Working Conditions

• Normal office working conditions.
• Occasional travel may be required for industry meetings, training, conferences, and stakeholder engagement activities.
• Position requires extensive computer-based analytical work and interaction with internal and external stakeholders.

Hoosier Energy is an Equal Opportunity Employer and prohibits discrimination on the basis of race, color, religion, national origin, sex (including pregnancy and gender identity), sexual orientation, age, ancestry, genetic information, disability, veteran status or any other characteristic protected by federal, state or local laws.