Quant Developer
Strobe is building the world's largest power plant: not a single site, but a distributed fleet of buildings, batteries, EVs, and generators that buy and sell power in real time across wholesale energy markets.
Own the environment our quants work in: the market, weather, and site data they research on, and the tooling that takes a forecast or strategy from a notebook to production. You'll know the data better than anyone, and build the systems that make research fast and trustworthy.
What you'd own
Clean, point-in-time datasets of wholesale prices, load, weather forecasts, and site telemetry, with revisions and publication times tracked
The research environment: data access, feature pipelines, and the libraries quants use to explore, fit, and compare models
Backtesting and simulation infrastructure that replays markets and asset constraints exactly as they were
The path to production: scheduled forecast and dispatch runs, versioned models, and monitoring that alerts when inputs or outputs look wrong
Data quality: gaps, late and revised data, timezone and DST edge cases, and reconciliation against ISO settlements
Close work with quants and traders on what they need next, and the judgment to build it once, properly
Strong fit if you have
Strong Python and SQL, and research or data platforms you built that others relied on
Experience with time-series data at scale, and an instinct for lookahead bias, leakage, and survivorship in historical data
Enough statistics and forecasting to understand what quants are building and what their tools need to get right
Experience in trading, market data, or another domain where a data error costs real money
The rigor to check your own numbers before someone else has to
Bonus points
Experience in power markets (NYISO, PJM, CAISO, ERCOT): LMPs, capacity, or ancillary services
Weather data and numerical weather prediction inputs
Optimization tooling (LP/MILP solvers) or battery and generator dispatch
Columnar and time-series stores (ClickHouse or similar)
Stack: Python / SQL / ClickHouse / AWS / Terraform / Grafana. AI-agent-native monorepo with deep investment in agent-enabled engineering efficiency.
Small team, high ownership, no layers.