Senior Growth Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the reliability and quality standards for an AI copilot integrated within a trading platform utilized by sophisticated investors.

• Design and establish evaluation systems that assess correctness, safety, latency, and regression risk across market analysis, portfolio/risk reasoning, and trading workflows, including order placement.

• Create and uphold curated golden sets, scenario suites, stress/adversarial cases, and market/regime-based testing corpora.

• Develop automated quality gates and regression workflows that prevent releases when critical metrics decline.

• Collaborate with engineering and product teams to define safe tool/action contracts, deterministic previews, confirmations, auditability, and expected assistant behavior.

• Manage model improvement cycles that involve data collection/labeling strategies, error taxonomy, adjustments to prompts/tooling, fine-tuning, or preference optimization.

• Design and implement AI monitoring and incident response protocols, including telemetry, alerting, root cause analysis (RCA), and forward-fix processes.

• Acquire a deep understanding of trading concepts and convey them clearly and accurately to users.

• Engage with the technology stack: Rust, TypeScript, Postgres, React, React Native, observability/telemetry tools, LLM APIs, model serving, and evaluation/training pipelines.

⛳️ Requirements

• A minimum of eight (8) years of experience delivering production software.

• Strong proficiency in any programming language.

• Solid understanding of computer science principles, testing methodologies, and systems design.

• Experience in building evaluation frameworks, test harnesses, and benchmark suites for complex systems (LLMs/agents/search/retrieval/ranking/recommenders).

• Proven experience in conducting model improvement cycles: dataset curation, labeling/quality assurance, offline experimentation, and implementing changes with measurable effects on benchmarks.

• Capability to define metrics, construct measurement pipelines, and influence engineering/product decisions through data insights.

• Comfort in working across the stack: troubleshooting model/tooling failures, instrumenting services, and collaborating with frontend/product teams on UX patterns that enhance safety and trust.

• High level of self-motivation and readiness to tackle unfamiliar challenges to resolve issues.

• Experience with fine-tuning, preference optimization, distillation, or prompt/compiler-style techniques to enhance tool-use reliability (bonus).

• Experience in developing domain-specific benchmarks and adversarial suites for high-stakes applications (bonus).

• Extensive experience with trading across various asset classes and margin types (bonus).

• Familiarity with Rust and performance-sensitive services (bonus).

• Experience in designing incident response strategies and service level objectives (SLOs) for ML/AI systems (bonus).

🏝️ Benefits

• Company equity.

• 401k matching.

• Gender-neutral parental leave.

• Comprehensive medical, dental, and vision insurance.

• Lunch stipends.

• Fully stocked kitchens.

• Happy hours.

• Excellent location.

• Stunning views.

• Collaborative culture.

• Equal opportunity workplace.