Senior Data Scientist

Join Traba, an early-stage startup, as a Senior Data Scientist. In this role, you will lead measurement and modeling for our agentic platform, define and improve agent quality, and build the evaluation, experimentation, and modeling foundations. You will work closely with engineering, product, and operations leadership, and provide strategic insights to senior leadership through in-depth statistical analysis and modeling. Additionally, you will mentor other scientists and analysts, and set the standards for measurement, modeling, and experimentation at Traba.

• Lead measurement and modeling for the agentic platform, defining and improving agent quality.
• Design, build, and maintain metrics, models, and reporting that track agent quality, reliability, adoption, and unit economics.
• Architect scalable analytics and modeling infrastructure to ensure data integrity, governance, and accessibility.
• Strong proficiency in Python and common ML and statistics libraries (e.g., scikit-learn, PyTorch, pandas, statsmodels)
• Education: BS/MS/PhD in data science, statistics, machine learning, computer science, mathematics, economics, or a related quantitative field (or equivalent work experience)
• Strong proficiency in SQL
• Self-Motivation: Ability to work independently and as part of a team in a fast-paced startup environment
• Collaboration Skills: Strong ability to work across departments, identifying and prioritizing analytics problems to deliver actionable insights
• Experience with LLM evaluation and observability tools like Langfuse, Braintrust, or internal harnesses, and with building automated evaluators
• Experience designing and analyzing experiments (A/B testing) and applying statistical inference or causal methods
• Communication Skills: Excellent data storytelling skills to effectively engage with stakeholders
• Technical Skills:
• Experience: 4-8 years in data science, machine learning, applied statistics, or quantitative research, with 2+ years of hands-on work modeling or measuring LLM- or agent-based systems in production
• Curiosity and Initiative: Intense curiosity to ask “why?” and use data to find answers, combined with a “no task too small” mentality
• Experience with notebook tools like Jupyter, Hex, Hyperquery, or equivalent
• Experience with modern data stack tools like dbt or equivalent
• Experience building internal agents or MCP servers for analytics workflows, or prior work at a vertical AI or AI-native data company (e.g., Hex, Omni, dbt)
• Experience fine-tuning, distilling, or rigorously evaluating LLMs, or applying causal inference and experimentation at scale