Data Scientist
San Francisco, CA · HybridFull-time$120–155K/yrPosted 4mo agoStill listed 3 days ago
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Job overview
Verse Inc. is hiring a Data Scientist. Verse is building an energy intelligence platform that helps large energy consumers secure faster, cheaper, and cleaner power by combining real-time control of assets with full portfolio visibility, backed by leading venture partners and pioneering grid‑scale technology.
Key focus areas include Build and improve renewable generation, storage dispatch, and energy price prediction models, Scope problems with product, engineering and customer teams and design solutions, and Integrate research outputs into cloud‑based production environment using Python.
Successful candidates bring Master's In Quantitative Field and Bachelor's Degree And 2+ Years Of Energy Sector Experience. Important skills include Machine Learning, Statistical Modeling, Python, NumPy, Pandas, and scikit-learn. Preferred (not required): Mathematical Optimization, Probabilistic Forecasting Models, and Quantifying Uncertainty.
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Full job description
Location: San Francisco (Hybrid in SF highly preferred, US only)
What is Verse?
The race to AI has become the race to power. Every breakthrough in artificial intelligence depends on one thing: access to electricity. But across the country, aging grid infrastructure and years-long interconnection queues are slowing the deployment of the data centers that will power the next generation of innovation. Solving this challenge isn't just about energy—it's about unlocking the future of AI.
At Verse, we're building the energy intelligence platform for the AI economy. Our software helps the world's largest energy consumers achieve faster, cheaper, and cleaner power by combining real-time control of energy assets with complete visibility into their energy portfolio. Backed by Bessemer Venture Partners, GV, Coatue, and NVIDIA, and built by pioneers in grid-scale batteries, energy markets, and enterprise software, we're redefining how the world's most ambitious organizations access and manage energy.
The Role
Verse is seeking a Quantitative Analyst to join our Data Science Team. In this position, you will own research projects end-to-end from problem formulation through model development to production integration. Your work feeds directly into Aria and into decisions our customers make about how to procure, dispatch, and hedge their energy assets. For example, you might spend a cycle backtesting financial performance of renewable energy projects, encoding bespoke energy contract terms into reusable and scaled models, or developing a probabilistic model for medium-term energy price scenarios.
Key Responsibilities
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Model & Forecast: Build and improve models for renewable generation, storage dispatch, and energy price prediction using machine learning, statistical methods, and optimization techniques.
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Own Research Projects: Scope problems with product, engineering and customer teams, design solutions, validate results against industry benchmarks, and communicate findings clearly to both technical and non-technical audiences.
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Software Development & Productionization: Integrate research outputs into Verse’s cloud-based production environment; write clean, well-documented Python code and leverage AI coding tools to accelerate development.
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Develop Domain Expertise: Build foundational knowledge of electricity markets and renewable energy trends; develop an understanding of key drivers (e.g., load growth, market rule changes, and renewable deployment) and learn to incorporate relevant insights into renewable energy PPA modeling and analysis. What We're Looking For (Minimum Qualifications)
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Master's degree in a quantitative field (engineering, computer science, economics, mathematics, operations research, physics, or similar); or
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Bachelor’s degree and 2+ years of energy sector experience
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Solid foundations in machine learning and statistical modeling
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Proficiency in Python, including scientific computing libraries (NumPy, pandas, scikit-learn)
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Familiarity with wholesale electricity market fundamentals and renewable energy technologies
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Ability to communicate technical findings clearly to both technical and non-technical audiences What Will Make You Standout (Preferred Qualifications)
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Direct experience with US or European wholesale electricity markets or utility tariff structures
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Experience with energy procurement, power purchase agreements, or risk management
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Experience modeling the operational and/or economic behavior of solar, wind, or energy storage
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Foundational knowledge of mathematical optimization
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Experience shipping models to production in a commercial or research environment
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Experience developing probabilistic forecasting models and quantifying uncertainty
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A PhD in a relevant quantitative field. What Makes Verse a Great Place to Work?
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Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
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Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
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Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
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Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations Base Pay Range
$120,000 - $155,000
This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.
Benefits and Employee Perks
- Competitive compensation and equity grant at a high-growth start up
- Comprehensive benefits package including medical, dental and vision insurance, and 401k
- Flexible hours and unlimited PTO
- Diverse and inclusive working environment Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.
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