Respondology is looking to solve the problem of measuring, safeguarding, and scaling excellence in their products by defining the quality bar and building experimentation and evaluation systems.
Requirements
- Strong expertise in Python and data wrangling with pandas/polars
- Solid SQL and data modeling skills
- Hands-on experience with SQL, Python, and modern data tools
- Familiarity with workflow orchestration and modern data tooling
- Experience with Snowflake (bonus points)
- Hands-on experience building and maintaining evaluation suites and guardrails that prevent regressions
- Ability to translate business goals into measurable product quality metrics and leadership-facing KPIs
Responsibilities
- Formalize quality metrics for Respondology’s products (using golden sets where possible and pragmatic heuristics when needed)
- Make business and product metrics easily accessible for leadership via reliable pipelines and dashboards
- Build internal tooling for robust experimentation
- Create systems that make accidental regressions hard, such as pre-merge evaluation suites and automated guardrails
- Set up pipelines for ongoing quality monitoring and reporting
- Pitch in on data engineering needs across our Postgres and OpenSearch stack today, and help lead a future warehouse effort and orchestration rollout
- Run segment-specific experiments to understand heterogeneous impact
Other
- Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering, or related technical field—or equivalent professional experience
- 5+ years of professional experience as a Data scientist or in a similar role
- Excellent communication skills with both technical and non-technical stakeholders
- A proactive, collaborative mindset working with Product, Eng, CS, and RevOps
- Ability to work in a fast-paced startup or scaling SaaS environment
