Director of Data Science - Modo Energy
Austin, TX
About the Job
At Modo Energy, we're on a mission to build the information architecture for the energy transition - we want to be the only place to come to for information on the global journey to net zero. Take a look at our platform, where we provide open access to an array of content on the energy transition.
We're a dedicated and passionate team building a category-defining business, working on one of the world's most important priorities. We are looking for individuals who love product-building, want to work with pace at a mission-oriented startup, and will collaborate with us in shaping the culture of a rapidly growing team.
The role
As a Director of Data Science at Modo Energy, you will be responsible for leading a team that analyzes complex energy market data and builds long-term forecast models to predict potential revenue streams for BESS, helping our clients make investment, strategic and operational decisions for their BESS portfolios.
Responsibilities:
- Help shape and execute the strategic vision for data science and modeling at Modo Energy, ensuring alignment with broader business goals and the energy market landscape.
- Hire, manage, and mentor a team of data scientists and analysts to deliver high-quality forecasts.
- Ensure scalable and maintainable deployment of data science models, working within cloud environments like AWS.
- Present complex data insights in a clear, compelling manner to both technical and non-technical stakeholders, supporting decision-making at the highest levels.
- Collaborate with other teams to ensure data insights drive key business decisions, from customer success to product development and external client-facing initiatives.
- Staying updated on emerging trends and regulations within the energy storage market to inform key model developments. .
- Represent Modo Energy at industry events, conferences, and in client meetings to communicate the value of Modo's data-driven insights and solutions.
Qualifications:
- 7+ years of experience in data science, with a focus on using Python (or another programming language such as R, C++, or Java) and the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.).
- A degree in a quantitative field such as mathematics, engineering, computer science, physics, or a related discipline.
- Proven leadership experience, managing and mentoring data science and modeling teams, and driving impactful data science initiatives.
- Strong quantitative skills and experience in solving complex technical problems using data analysis, machine learning, and optimization techniques.
- Proven experience with optimization using linear programming, with a strong preference for Python-based implementations.
- Hands-on experience with cloud environments (e.g., AWS) for deploying data science models.
- Deep understanding of electricity markets, grid operations, and pricing mechanisms.
- Excellent technical communication skills, with the ability to explain complex data science concepts to non-technical stakeholders.
- A self-starter attitude, with an eagerness to dive into new challenges and the ability to work independently and as part of a team.
Required Experience:
You should have strong, demonstrable experience in (at least one of) the following areas:
- Modeling - Solid understanding of optimization methodologies and linear programming, including building and refining mathematical models for decision-making.
- Market knowledge - Broad and deep knowledge of the inner workings of a US ISO, including market mechanisms, policy developments, and the opportunities for flexible grid infrastructure.
Preferred Skills:
- Experience in the energy markets and battery energy storage systems (BESS).
- Advanced knowledge of mathematical modeling and its application to long-term, time-series forecasting problems.
- Public-speaking experience or the ability to represent the company in industry events, webinars, and conferences.
- Strong project management skills, with experience leading cross-functional initiatives.
- Experience managing or contributing to complex, evolving software projects, with a focus on long-term product development and iterative improvements.
- A self-starter attitude, with an eagerness to dive into new challenges and the ability to work independently and as part of a team.
Important Details:
- This role can be based in either Austin, TX or New York, NY.
- We work in a Hybrid Environment: You split your time between working from home and working in our Austin or New York offices (Tuesday through Thursday).
- Competitive salary and benefits package, including health, dental, and vision insurance, 401k matching, paid time off, and other perks.
If you're passionate about data science and want to lead a talented team while driving the energy transition forward, we'd love to hear from you. Apply now and join our growing team at Modo Energy!
Modo Energy is an equal-opportunity employer. Our employment decisions are made on the basis of qualifications, merit, and business need. We do not discriminate against age, national origin, physical or mental disability, race, religion, pregnancy, sexual orientation, gender identity, veteran status, or any other characteristic protected by federal, state, or local law. If you need assistance or a reasonable accommodation with an application or the interview process please contact us via email at careers@modo.energy.
What you can expect from Modo
We want to attract and retain the best talent at Modo, and we give our people the freedom and opportunity to develop themselves and flourish.
We are committed to building a diverse and inclusive team at Modo, as we believe a variety of backgrounds, skills and interests is what makes our company stronger. If you share our values and our enthusiasm for supporting the transition to greener energy systems, we encourage you to apply. We have a number of positions open which could be for a range of backgrounds and experience levels. Please get in touch if you are interested and you don't meet all the requirements, or if you exceed them!
