Senior / Staff Data Scientist, Applied AI
Clear Street is hiring a Senior/Staff Data Scientist to own the reliability of an AI copilot embedded in its trading platform — building evaluation systems, benchmarks, quality gates, and model improvement loops. Core work spans LLM evals/telemetry plus its stack of Rust, TypeScript, Postgres, and React.
- Compensation
- $200K–$500K / yr
- Location
- Remote
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data science
- Posted
Skills
Must have
- At least 8 years of experience shipping production software; strong proficiency with any programming language
- Strong knowledge of computer science fundamentals, testing methodology, and systems design
- Experience building evaluation frameworks, test harnesses, and benchmark suites for complex systems (LLMs/agents/search/retrieval/ranking/recommenders)
- Experience running model improvement cycles: dataset curation, labeling/QA, offline experimentation, and deploying changes with measurable benchmark impact
- Ability to define metrics, build measurement pipelines, and drive engineering/product decisions from data
- Comfort working across the stack: debugging model/tooling failures, instrumenting services, partnering with frontend/product on UX for safety and trust
- High degree of self-motivation and willingness to jump into unfamiliar areas
Nice to have
- Experience with fine-tuning, preference optimization, distillation, or prompt/compiler-style techniques for improving tool-use reliability
- Experience creating domain-specific benchmarks and adversarial suites for high-stakes applications
- Deep experience with trading across asset classes, margin types, etc.
- Experience with Rust and performance-sensitive services
- Experience designing incident response and SLOs for ML/AI systems
Full description
Clear Street is modernizing the brokerage ecosystem. Founded in 2018, Clear Street is a diversified financial services firm replacing the legacy infrastructure used across capital markets.
We started from scratch by building a completely cloud-native clearing and custody system designed for today's complex, global market. Our platform is fully integrated with central clearing houses and exchanges to support billions in trading volume per day. We've agonized about our data model abstractions, created horizontal scalability, and crafted thoughtful APIs. All so we can provide a best-in-class experience for our clients.
By combining highly-skilled product and engineering talent with seasoned finance professionals, we're building the essentials to compete in today's fast-paced markets.
**The Team:
**The mission of the Clear Street Active team is to provide best execution for every asset class in every market. Active is currently building a new, state-of-the-art, cloud-based trading platform providing high-performance traders access to liquidity venues across multiple asset classes, cutting-edge charting capabilities, and sophisticated order handling with the flexibility to service both the active trader and institutional workflows.
The Role:
-
You will own the reliability and quality bar for an AI copilot embedded in an trading platform used by sophisticated investors
-
You will design and build evaluation systems that measure correctness, safety, latency, and regression risk across market analysis, portfolio/risk reasoning, and trading workflows (including order placement)
-
You will develop and maintain benchmarks: curated “golden sets,” scenario suites, stress/adversarial cases, and continuously refreshed market/regime-based test corpora
-
You will build automated quality gates and regression workflows that block releases when key metrics degrade
-
You will partner with engineering and product to define safe tool/action contracts (deterministic previews, confirmations, auditability) and ensure predictable assistant behavior
-
You will own model improvement loops tied to evals: data collection/labeling strategies, error taxonomy, prompt/tooling changes, and when appropriate, fine-tuning or preference optimization to measurably improve benchmark performance
-
You will design and operate monitoring + incident response for AI: telemetry, alerting, RCA, and “fix-forward” processes
-
You will develop a deep understanding of trading concepts (margin, shorting, portfolio margin, risk, execution) and how to express them accurately and understandably to users