Data Scientist

Key Skills

Data Analytics, Data science techniques, Finance, Keras software library, Machine learning techniques, matplotlib, NumPy, Pandas, Python Programming, PyTorch, Scikit-learn, SciPy, seaborn, Statistics, TensorFlow, XGBoost

Job Description

The Data Scientist (Energy Analytics) will be involved in various functions including short-term and long-term renewable power portfolio forecasting. The data scientist will apply their skills and knowledge in data science, machine learning, statistics, and programming to explore the solutions for improving energy/LMP forecasting performance, benchmarking competition, and backtesting bidding and offer strategies. The successful candidate will be an integral part of a team responsible for optimizing the profitability of a growing portfolio of operating assets. This position will primarily support Asset Management and coordinate with a variety of additional internal and external counterparties including Transmission Analytics, Power Marketing, Risk, Finance, Operations, and Capital Markets.

Responsibilities

• Create machine learning pipelines for forecasting (e.g., energy generation and load forecasting, LMP, congestion forecasting). This includes API testing, data exploration, identifying/processing data quality issues, data cleaning, model training, and tuning the model parameters or features to improve its accuracy or reduce its complexity, validation, and model deployment using machine learning best practices.
• Conduct in-depth analysis of market conditions using historical and real-time data (e.g., from power flow, ISO system data, third-party APIs) to create data pipelines to improve SB Energy’s bidding and offer strategy performance. Provide data inputs to Asset Management to optimize bidding strategies for energy markets such as CAISO, ERCOT, PJM, and MISO.
• Create back-testing pipelines to regularly back-test and evaluate the effectiveness of bidding strategies for operating projects.
• Evaluate the impact of weather uncertainty on energy markets. Analyze historical weather data, forecast models, and market behavior to assess risks of over and under-production and inform decision-making.
• Identify the impact of congestion on operating projects and proactively optimize bidding strategies. Work closely with Transmission analytics to refine power flow models and congestion analysis to provide insight into revenue optimization.
• Forecast curtailment of operating projects. Identify potential impacts of low load, high generation, hydro conditions, and adverse weather events in the ISO.
• Coordinate with Asset Management, Power Marketing, and Risk Group on operating projects performance analysis and be the driver for data-driven decision making.
• Provide Asset Management with appropriate data to maintain accurate revenue forecasts by analyzing market trends, historical data, and other relevant factors. Conduct thorough analysis and modeling to ensure realistic revenue goals are set and achieved.

Qualifications/Requirements

• Bachelor's Degree in a quantitative discipline (e.g., Electrical and Computer Engineering, Computer Science, Finance, Statistics, Economics, Math, or related field).
• 5+ years of working experience in energy and power Markets required with experience in CAISO and ERCOT a plus.
• Proficient with Python. Strong working experience with Python data science and machine learning packages, such as NumPy, Pandas, Matplotlib, Seaborn, Plotly, bokeh, Scipy, stats model, XGBoost, Scikit-Learn, Keras, TensorFlow, PyTorch, or-tools, Pyomo.

• The candidate is familiar with the technical aspects of power systems, including power flow modeling, basis, congestion, transmission network, and the impact of generation (solar, wind, gas, coal) and load on LMPs.
• Experienced individual with expertise in multivariate time series forecasting, stochastic optimization, and Monte Carlo simulations.
• The candidate needs to have experience in supporting energy bidding and offer optimization, congestion management, and/or commercial decision-making.

Location: Houston, TX, San Francisco / Bay Area, CA, and Denver, CO are preferred locations. Open to remote work.

The position requires up to 10% domestic travel.

Base Pay - $120,000 - $130,000

Actual compensation packages are based on several factors that are unique to each candidate, such as skill set, experience, certifications, specific work location, and other non-discriminatory factors permitted by law. Base pay may vary per location due to differences in the cost of living.

The total compensation package for this position may also include an annual discretionary bonus, full Health & Wellness Benefits package, generous Long Term Incentive plan designed with our partnership mentality in mind, and other applicable incentive perks as outlined in any formal offer made. The final compensation package will be discussed with the candidate during the final stages of the hiring process.

Our Health & Wellness Benefits

SB Energy’s Benefits programs are designed to support our team members and their families while keeping their well-being, happiness, and varying needs in mind. SB Energy employees may enroll in our benefits programs and take advantage of customized perks and offerings, including those designed to support families, however defined. We offer the following benefits to all team members:

• Comprehensive Medical, Dental, and Vision insurance: 100% premium covered by the company, for employees and dependents​
• Long-Term Disability (LTD), Life Insurance, AD&D and Voluntary Legal ​Insurance Plan
• Competitive Retirement Benefits with 401(k) company match
• Generous Paid Time Off and 11 Paid Company Holidays
• Flexible working arrangements
• 12 weeks fully paid Parental Leave
• Flexible Spending Account (FSA) –​ Medical & Dependent FSA; Transit & Commuter FSA with employer contributions
• Mental Health Wellness Offerings
• Discounted Physical Wellness plan & Pet Insurance
• Monthly reimbursement for Phone/Internet/Data
• Phone Equipment Purchase Benefits
• Thoughtful Hybrid Workplace Set-up Benefits