Senior Director of Data Science and Analytics, ServiceTitan

• 8+ years in data science or applied AI/ML, with 5+ years leading and growing teams
• Strong background managing analytics teams
• Demonstrated track record in influencing internal operational decisions based on ML systems (e.g. forecasts and lead scores)
• Strong foundation in statistics and ML, plus depth in modern AI: LLMs, agentic systems, orchestration (e.g., tool use, MCP), retrieval, and the evaluation practices these require
• Proven expertise in analytics- driving decisions through deep analysis
• Fluency in SQL and Python; familiarity with modern data and AI stacks (cloud warehouses, dbt, LLM/agent deployment pipelines)
• Proven ability to partner with non-technical executives and translate ambiguous business problems into tractable work
• Comfort operating in a fast-moving, data-rich environment where decisions carry real operational and cost consequences
• Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway

Desirable

• We're seeking a Director of Data Science for Operations to lead data science and applied AI across two connected domains: our operational core and finance analytics. You'll partner with operations and finance leadership to turn complex data into intelligent systems, decisions, and measurable impact—spanning internal operational efficiency and critical business analytics. This is a player-coach leadership role: you'll set technical direction, but also be hands on delivering projects
• This role has significant latitude to work on and invent new high ROI projects- the only limit is your creativity
• Own the data science and applied AI roadmap for G&A—agentic systems, forecasting, lead scoring, and decision-support that improve throughput, reliability, and unit economics. Build agents and AI workflows that don't just predict but act
• Lead, hire, and develop a data science and analytics team executing on operational and product-facing work; set standards for technical rigor, evaluation, and production quality
• Partner with operations, and product leadership to identify high-leverage problems, frame them, and translate them into operational decisions and shipped AI capabilities
• Responsible for our finance analytics team that supports all of finance - accounting, FP&A, and pricing
• Collaborate with data engineering, machine learning engineering, and platform teams on the infrastructure, data quality, orchestration, tooling, and guardrails these systems depend on
• Communicate findings and recommendations to executive stakeholders, balancing technical depth with business clarity
• Champion an AI/agent-first way of working within the team—both as a hands-on technical leader (e.g., Claude Code) and by inventing agentic systems that make the team faster