Sr. Data Scientist II

We’re reinventing the market research industry. Let’s reinvent it together.

At Numerator, we believe tomorrow’s success starts with today’s market intelligence. We empower the world’s leading brands and retailers with unmatched insights into consumer behavior and the influencers that drive it.

Numerator is seeking a Sr. Data Scientist II (Bayesian Modeling) to help build, enhance, and scale data science services across our rapidly evolving data platform. You’ll work end-to-end on initiatives that turn massive proprietary datasets into impactful, production-grade solutions.

This is a highly autonomous, product-focused role. You’ll partner with Product, Data, and Engineering teams to translate customer needs into data-driven products, analytics methodologies, and new offerings that drive measurable business impact.

How You'll Spend Your Time:

• Lead the design and delivery of complex Bayesian and probabilistic modeling pipelines, from methodology through production
• Set technical direction on hard modeling problems and make the key methodological calls, with a high degree of autonomy
• Work closely with Product, GTM, Data, and Engineering to turn models into reliable, production-grade solutions the business can depend on
• Help the whole team get better — mentor other data scientists, share your approach openly, and raise the bar for how the group reasons about uncertainty and Bayesian methods
• Communicate methods, results, and tradeoffs clearly to both technical and non-technical audiences

What You'll Bring to Numerator

• Strong foundation in Bayesian inference and probabilistic modeling — e.g. hierarchical / multilevel models, state-space and time-series models, graphical models, MCMC/HMC, variational and other approximate inference
• Experience applying these methods to real, messy, production data — not only research or coursework
• Comfort reasoning about uncertainty, calibration, and model validation
• Facility with large or structured datasets and the computational side of inference at scale
• Strong Python, and fluency in a modern probabilistic-programming and numerical-computing stack — NumPyro, PyMC, Stan, JAX, dynamax, or similar. We hire on the ideas, not on exact tooling
• Track record of shipping statistical models into production
• BS or PhD in Statistics, Math, Economics, Physics, CS, or a related quantitative field
• 8+ years of industry experience as a data scientist (or equivalent role/work) with a BS in the above-mentioned areas, or 5+ years of industry experience with a PhD in a quantitative field
• Clear communication with both technical and non-technical audiences

Nice to Haves:

• Diagnosing and debugging large Bayesian models — convergence and divergence issues, pinning down which part of a big model is misbehaving, and knowing which inference method to reach for
• Weighting a non-representative survey or panel sample up to a known population, and a feel for where those adjustments break down
• Hierarchical models spanning multiple crossed or overlapping groupings — relationships that bridge hierarchies, not just a single nested tree
• Experience with graph or network models, or modeling relational / graph-structured data
• Measurement-error modeling, or reconciling multiple imperfect data sources
• CPG / FMCG / retail experience, or work with user-level purchase or panel data