Data Scientist (Bayesian Inference)

Numerator Career Center; Chicago (IL); On-site; USD 110,000 - 170,000; Full time

Job summary

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

This is a growth-track, product-focused role. You’ll collaborate with Product, Data, and Engineering teams to learn how customer needs translate into data-driven products, analytics methodologies, and new offerings that drive

Responsibilities

• Contribute to the implementation and delivery of Bayesian and probabilistic modeling pipelines, from methodology research through production, with guidance from senior team members
• Execute on individual tickets independently and take on small epics with mentorship and guidance
• Work closely with Product, GTM, Data, and Engineering to turn models into reliable, production-grade solutions the business can depend on
• Actively participate in the team's learning culture (journal club, analysis reviews, standups) and seek feedback to continually level up your craft in Bayesian methods and reasoning about uncertainty
• Communicate methods, results, and tradeoffs clearly to both technical and non-technical audiences

Job description

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

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

How You'll Spend Your Time:

• Contribute to the implementation and delivery of Bayesian and probabilistic modeling pipelines, from methodology research through production, with guidance from senior team members

• Execute on individual tickets independently and take on small epics with mentorship and guidance

• Work closely with Product, GTM, Data, and Engineering to turn models into reliable, production-grade solutions the business can depend on

• Actively participate in the team's learning culture (journal club, analysis reviews, standups) and seek feedback to continually level up your craft in Bayesian methods and reasoning about uncertainty

• Communicate methods, results, and tradeoffs clearly to both technical and non-technical audiences