Jupiter seeks to hire a highly motivated and experienced professional as its Senior Data Scientist. The successful candidate will be primarily responsible to develop, deploy and continuously improve machine learning-based price forecasting models that support daily trading and battery dispatch optimization decisions across ISO and wholesale power markets. The position is also expected to spearhead other data science initiatives which will enhance Jupiter’s market operations platform.

This role will be based out of our Houston, Texas office and will be subject to our return-to-office policy which currently requires employees come in 3+ days per week.

Key Responsibilities

• Develop and deploy machine learning and AutoML models for forecasting energy and ancillary services prices across ISO and wholesale power markets leveraging a strong foundation in mathematics, statistics and model architecture.

• Lead end-to-end machine learning initiatives, including building of forecasting pipelines, data preparation, feature engineering, model development, validation, deployment, monitoring and retraining.

• Research, evaluate and implement emerging AI and machine learning technologies, identifying opportunities to improve forecasting accuracy, operational efficiency and business value.

• Promote best-practices and internal understanding of forecasting processes, including assessments of forecast inputs, analysis of forecast results and continuous improvement of model accuracy, performance, and reliability.

• Identify appropriate model performance metrics including rigorous back testing and model evaluation using both statistical metrics and business focused performance metrics, in addition to benchmarking of internal model performance against external providers.

• Collaborate with traders, analysts, and optimization teams to evaluate impact of forecast improvements on trader actions, portfolio performance, and to integrate forecasts into decision-support and dispatch optimization systems.

• Translate complex technical concepts into clear, actionable business insights, effectively communicating model methodologies, results, and recommendations to technical and non-technical stakeholders.

• Contribute to the overall performance of the Data Science team, proving leadership for the deployment of AI and machine-learning technologies and contributing to the development of junior team members

Additional Responsibilities

• Develop probabilistic forecasts, scenario analysis, and uncertainty metrics to support dispatch optimization, bidding decisions and risk management.

• Perform market analysis to identify emerging trends, regime shifts, congestion patterns, scarcity events, and other drivers of price formation in wholesale electricity markets.

• Build and validate analytical tools and dashboards that improve visibility into market conditions, forecast performance, and asset opportunities.

• Lead investigations into forecast performance, model misses, and changing market dynamics, translating findings into model enhancements and actionable business recommendations.

• Collaborate with cross-functional teams, including Trading, Market Analytics, and Market Operations to identify business challenges and develop scalable, data-driven solutions.

Requirements

• Bachelor's or advanced degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field. Advanced degree preferred.

• 6+ years of hands-on experience in data science or machine learning, with a demonstrated record of developing and deploying production-level solutions.

• Experience developing forecasting models in wholesale power markets, energy trading, commodity markets, financial markets, or other complex time-series forecasting environments is preferred.

• Strong mathematical and statistical foundation, with a deep understanding of machine learning algorithms, model architectures, optimization methods, and hyperparameter tuning.

• Proven experience developing, evaluating, and deploying machine learning models using Python and modern frameworks such as XGBoost, LightGBM, TensorFlow, PyTorch, or scikit-learn.

• Demonstrated success managing the full machine learning lifecycle, including model development, deployment, monitoring, and maintenance, following MLOps and DataOps best practices.

• Strong Python programming skills, software engineering practices, and experience developing scalable data pipelines and automated processes.

• Extensive hands-on experience with cloud platforms and big data technologies, particularly Azure, AWS, Databricks, Apache Spark, and distributed computing environments.

• Strong analytical and problem-solving skills, with the ability to work independently, troubleshoot complex technical challenges, and deliver reliable solutions.

• Excellent communication skills, with the ability to explain sophisticated analytical methodologies and technical findings clearly to business stakeholders.

• Ability to work effectively in a collaborative, cross-functional environment.

In addition to base pay, the total annual compensation package may also include eligibility to participate in our bonus and equity programs. Jupiter Power offers a variety of other benefits including paid time off, 401k with limited matching, health benefits (medical, dental, and vision), life insurance, disability insurance, and flexible spending accounts.

Jupiter Power does not discriminate based on a candidate's race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a protected veteran, disability, or any other protected class.