Forecast Software Engineer: Stats Modeling & Optimization

Search Services; Houston (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Search Services is seeking a Forecast Software Engineer — Statistical Modeling & Optimization to build analytical software for ERCOT forecasting, benchmarking, and confidence scoring. You will translate established methodologies and grid-model outputs into reliable production software, blending software engineering with applied statistics and uncertainty measurement.

The role requires strong Python production skills, experience in time-series validation and backtesting, and the ability to

Qualifications

• Bachelor’s or Master’s degree in statistics, applied mathematics, operations research, computer science, engineering, econometrics, data science, or a related field.
• Strong production-level Python skills.
• Strong foundation in applied statistics and probability.
• Experience developing quantitative, analytical, or forecasting software.
• Proficiency with NumPy, Pandas, SciPy, scikit-learn, SQL, and Git.
• Experience with time-series validation, backtesting, uncertainty measurement, and model-performance analysis.
• Ability to translate domain-expert requirements into reproducible software.
• Strong testing, debugging, and technical-documentation skills.

Responsibilities

• Develop ERCOT congestion, basis, and nodal-price forecasting services.
• Implement simplified SCED, economic-dispatch, and constraint-aware optimization calculations.
• Integrate grid topology, transmission constraints, generator characteristics, load and renewable forecasts, fuel curves, and market data.
• Build rigorous historical replay and backtesting processes while preventing data leakage and look-ahead bias.
• Measure forecast accuracy, bias, stability, calibration, and uncertainty using appropriate statistical methods.
• Develop confidence-scoring methodologies based on model performance, data quality, forecast horizon, scenario volatility, model agreement, and other relevant factors.
• Build standardized frameworks for comparing internal and third-party forecasts.
• Develop ensemble-model comparisons, benchmark reports, and model-performance scorecards.
• Implement scenario and sensitivity analysis for fuel prices, load growth, renewable output, generator availability, outages, and transmission constraints.
• Develop documented APIs and batch-processing workflows for forecasting and confidence scores.
• Write maintainable, tested, version-controlled Python software and automated unit, integration, regression, and statistical tests.
• Document methodologies, formulas, assumptions, dependencies, limitations, and model versions.

Skills

Python programming

Statistics & probability

Forecasting software development

Time-series validation

SQL

Git

Education

Bachelor’s or Master’s degree in statistics / math / OR / CS / engineering

Tools

NumPy

Pandas

SciPy

scikit-learn

Pyomo

Gurobi/CPLEX/OR-Tools

PostgreSQL

Docker

REST APIs

Job description

Search Services is seeking a Forecast Software Engineer — Statistical Modeling & Optimization to build analytical software for ERCOT forecasting, benchmarking, and confidence scoring. You will translate established methodologies and grid-model outputs into reliable production software, blending software engineering with applied statistics and uncertainty measurement.

The role requires strong Python production skills, experience in time-series validation and backtesting, and the ability to