Application Guide

How to Apply for Staff Data Scientist

at Lunar Energy

🏢 About Lunar Energy

Lunar Energy is at the forefront of the clean energy transition, using AI to optimize solar and battery systems for homes. Their mission to empower homes with sustainable energy is both impactful and aligned with the growing demand for smart grid solutions. Working here means contributing to a greener future while tackling cutting-edge challenges in energy markets.

About This Role

As a Staff Data Scientist, you will develop algorithms that enable fleets of distributed energy resources (DERs) to trade in wholesale electricity markets, optimizing for profitability and grid stability. Your work directly impacts the viability of renewable energy by making it economically competitive, while also managing real-time operations and risk.

💡 A Day in the Life

A typical day might start with a stand-up to discuss real-time fleet performance and any market anomalies, then dive into coding a new optimization model for battery trading. After lunch, you might analyze historical price data to refine a forecast, and end the day reviewing risk metrics for the next day's trading strategy.

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Interview Prep

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🎯 Who Lunar Energy Is Looking For

  • Has 5+ years of experience in quantitative roles (e.g., quantitative developer, data scientist, risk analyst) with a track record of building production-grade optimization or forecasting systems.
  • Holds an advanced degree (MSc/PhD) in a quantitative field like physics, mathematics, or statistics, and can apply rigorous mathematical thinking to real-world energy problems.
  • Possesses deep expertise in Python, Julia, or OCaml, and is proficient with libraries like pandas, TensorFlow, or NumPyro for time series analysis, optimization, and probabilistic modeling.
  • Understands energy markets, DER behavior (e.g., batteries, solar), and has experience with control theory, signal processing, or decision-making under uncertainty.

📝 Tips for Applying to Lunar Energy

1

Tailor your resume to highlight specific projects involving forecasting, optimization, or control of energy systems or similar physical assets.

2

In your cover letter, explicitly connect your experience with Python/Julia to building scalable algorithms for real-time trading or risk management.

3

Demonstrate familiarity with wholesale electricity markets (e.g., PJM, CAISO) and how DERs can participate (e.g., demand response, frequency regulation).

4

Share a GitHub repo or portfolio with relevant code, such as a time-series forecasting model or an optimization solver for battery scheduling.

5

Mention any experience with probabilistic programming (e.g., NumPyro, PyMC) or uncertainty quantification, as the role emphasizes quantifying risk.

✉️ What to Emphasize in Your Cover Letter

['Emphasize your quantitative background and ability to model complex systems (e.g., physical asset behavior, market dynamics).', 'Highlight your experience with optimization and decision-making algorithms under uncertainty, especially in energy or similar domains.', 'Show passion for sustainability and how your skills can help Lunar Energy achieve its mission of AI-driven home energy management.', "Mention any direct experience with battery/solar systems or DER aggregation, and how you've handled real-time operations."]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read about Lunar Energy's product offerings (e.g., home battery systems, AI platform) and how they integrate with smart home devices.
  • → Understand the basics of wholesale electricity markets (e.g., day-ahead vs. real-time, LMP) and how DERs can participate (e.g., via aggregators).
  • → Look into recent trends in virtual power plants (VPPs) and how companies like Lunar Energy are using AI to manage distributed assets.
  • → Check if Lunar Energy has published any technical blog posts or white papers on their algorithms or energy trading strategies.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you model the physical behavior of a battery (e.g., state of charge, degradation) for use in market optimization?
2 Describe an optimization algorithm you've built for trading or scheduling under uncertainty (e.g., stochastic programming, MPC).
3 Walk through a forecasting project where you predicted energy prices, solar generation, or load; how did you handle seasonality and uncertainty?
4 How do you quantify and manage financial risk when operating a DER fleet in wholesale markets (e.g., value-at-risk, scenario analysis)?
5 Given a portfolio of home batteries, how would you design a control strategy to maximize revenue from frequency regulation while ensuring customer comfort?
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⚠️ Common Mistakes to Avoid

  • Don't focus solely on machine learning; this role emphasizes optimization, control, and risk—balance your application with these skills.
  • Avoid generic statements about 'passion for data science'; instead, show specific interest in energy markets and DER control.
  • Don't ignore the real-time operations aspect; highlight any experience with live systems, low-latency algorithms, or production deployments.

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Lunar Energy!

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