Senior Growth Data Scientist

Clear Street

WorldwideFully remoteFull TimeSeniorInformation Technology
USD 180,000–250,000 a yearPosted 1h ago

Why we think you can apply

Hiring model
Open worldwide · the employer states no country restriction
Work from
Anywhere, the UAE included

Posted 1 hour ago · apply link checked 51 minutes ago

About the role

Responsibilities

  • Own the reliability and quality bar for an AI copilot in a trading platform
  • Design evaluation systems measuring correctness, safety, latency and regression risk
  • Develop benchmarks, golden sets and adversarial test corpora
  • Build automated quality gates and regression workflows
  • Define safe tool and action contracts with engineering and product
  • Run model improvement loops tied to evals
  • Operate monitoring and incident response for AI systems

Requirements

  • At least 8 years shipping production software
  • Strong computer science fundamentals and systems design
  • Experience building evaluation frameworks and benchmark suites
  • Experience with model improvement cycles and dataset curation
  • Ability to define metrics and drive decisions from data
  • Comfort debugging across the stack

Preferred Qualifications

  • Experience with fine-tuning, preference optimization or distillation
  • Domain-specific adversarial benchmarks for high-stakes applications
  • Deep trading knowledge across asset classes and margin types
  • Experience with Rust and performance-sensitive services
  • Experience with incident response and SLOs for ML/AI systems

Benefits

  • Competitive compensation, company equity and 401k matching
  • Gender neutral parental leave and full medical, dental and vision insurance
  • Lunch stipends and in-office perks

About the Company

Clear Street is a diversified financial services firm building a cloud-native clearing and custody system for modern capital markets.

What we look for

  • At least 8 years shipping production software
  • Strong computer science fundamentals and systems design
  • Experience building evaluation frameworks and benchmark suites
  • Experience with model improvement cycles and dataset curation
  • Ability to define metrics and drive decisions from data
  • Comfort debugging across the stack
  • Experience with fine-tuning, preference optimization or distillation
  • Domain-specific adversarial benchmarks for high-stakes applications
  • Deep trading knowledge across asset classes and margin types
  • Experience with Rust and performance-sensitive services
  • Experience with incident response and SLOs for ML/AI systems
TypeScriptReactAutomationRustPostgreSQLMachine LearningData AnalysisLLMTelemetry
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