Senior Data Scientist

Jupiter Power LLC; Houston (TX); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Paid time off

401k with limited matching

Health benefits (medical, dental, and

Life insurance

Disability insurance

Flexible spending accounts

Job summary

Jupiter Power LLC in Houston seeks a Senior Data Scientist to develop, deploy, and continuously improve ML-based price forecasting models for ISO and wholesale power markets. You will lead end-to-end ML projects, build forecasting pipelines, and spearhead data science initiatives across Jupiter’s market operations platform.

The role requires strong Python skills, experience with ML frameworks, and a track record of deploying production models.

Qualifications

• 6+ years of hands-on data science experience with production-level solutions.
• Experience forecasting in wholesale power or time-series markets preferred.
• Strong mathematical and statistical foundation with ML algorithms and hyperparameter tuning.
• Proficiency in Python and ML frameworks (XGBoost/LightGBM/TensorFlow/PyTorch/scikit-learn).
• Experience with ML lifecycle, MLOps and DataOps practices.

Responsibilities

• Develop and deploy machine learning and AutoML models for energy price forecasting.
• Lead end-to-end ML initiatives including data prep, feature engineering, deployment, monitoring and retraining.
• Research and implement new AI/ML technologies to improve forecasting accuracy and efficiency.
• Communicate model methodologies and results clearly to technical and non-technical stakeholders.
• Mentor and develop junior team members and contribute to Data Science team performance.

Skills

Forecasting models

Python

ML/Ops

Cloud platforms

Statistical analysis

Data pipelines

Communication

Team collaboration

Education

Bachelor's degree or higher

Advanced degree preferred

Tools

XGBoost

LightGBM

TensorFlow

PyTorch

scikit-learn

Azure

AWS

Databricks

Apache Spark

Job description

Jupiter Power is a leading independent developer, owner and operator of utility-scale battery energy storage projects across the United States. Founded in 2017, the company's projects store electricity and deliver it back to the grid when it is needed most, helping support a more reliable and resilient power system. Jupiter Power has 19,700 MWh of projects operating, in construction or committed, and another 110,000 MWh in development across the country. The company has corporate offices in Austin and Houston, Texas and Chicago, Illinois. For more information, visit www.jupiterpower.io.

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.

Benefits

• paid time off
• 401k with limited matching
• health benefits (medical, dental, and vision)
• life insurance
• disability insurance
• flexible spending accounts

In addition to base pay, the total annual compensation package may also include eligibility to participate in our bonus and equity programs.

Equal Opportunity Employer

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.