Senior Data Scientist

Your role in the team

Our expectations of you

Qualifications

• You can reason empirically about cost, latency, and quality tradeoffs across model providers and make principled model selection decisions.
• You are comfortable owning production systems, not just building models, and take responsibility for reliability, performance, and outcomes.
• You write production-grade code in Python and SQL, and are familiar with ML lifecycle practices, orchestration, monitoring, and modern engineering standards (e.g., CI/CD, version control).
• You are familiar with LLM-specific observability: tracing chained LLM calls, monitoring token usage and cost, and instrumenting multi-step pipelines for reliability and debugging.
• You can translate ambiguous business problems into well-scoped DS/ML solutions, communicate trade-offs clearly, and operate effectively in fast-moving, uncertain environments.
• You bring a strong foundation in statistics and causal inference, including experimentation, hypothesis testing, and robust evaluation practices.
• You can define meaningful metrics and challenge misleading results, ensuring decisions are grounded in real business impact.
• You take ownership beyond your individual work, contributing to team standards, mentoring others, and raising the overall bar for Data Science.

Experience

• You have hands-on experience with NLP and LLM-based systems in user-generated, noisy, multilingual contexts - with clear judgment on when LLMs add value, when to prompt-engineer vs. fine-tune, and how to optimize prompts systematically at scale.
• You have experience owning data science solutions end-to-end, from problem definition to production, iteration, and continuous improvement.

What we offer