Data Scientist

Numerators Data Science team provides statistical and methodological leadership across the organization developing the methodologies tools and data products that support our products.

This is a wide-ranging applied data science role focused primarily on the consumer purchase panel underlying our largest products with opportunities to contribute to other complex data science initiatives across Numerators broader product portfolio. The work combines applied statistics data investigation methodology development and practical implementation. Many of the questions we tackle do not have a single observable right answer requiring us to combine statistical evidence product context and subject-matter judgment to understand tradeoffs and determine whether a solution improves the product as a whole. As your expertise grows you will take on increasingly complex work and have opportunities to deepen your technical expertise lead projects improve team practices and shape how we work.

• Design and implement statistical methodologies that improve the representativeness stability and quality of Numerators products.

• Develop data science solutions to problems involving consumer behavior panel composition and data quality using techniques such as sampling weighting statistical modeling classification predictive modeling anomaly detection and optimization.

• Build scalable Python and SQL solutions internal tools and data products that turn statistical methodologies into reliable production workflows.

• Develop metrics monitoring and validation frameworks to evaluate system performance and identify unexpected or unintended behavior.

• Contribute throughout the project lifecycle from problem definition and exploration through implementation testing deployment and ongoing evaluation.

• Work closely with Product Engineering Data Operations and business partners to shape requirements and develop solutions that are both statistically sound and practical to use.

• Communicate methodologies findings assumptions and tradeoffs clearly to technical and non-technical audiences.

• A bachelors or advanced degree in Statistics Mathematics Data Science Computer Science Economics Physics or another quantitative field or equivalent practical experience.

• Two to five years of industry experience developing and delivering data science solutions.

• A strong foundation in applied statistics with experience applying statistical modeling optimization or other quantitative methods to real-world data problems.

• Proficiency in Python and SQL including experience developing reusable well-structured code and working with large complex datasets.

• Comfort working through open-ended problems investigating unexpected results and developing solutions with guidance and collaboration along with the ability to communicate effectively with technical and non-technical partners.

• Familiarity with survey research or consumer panelsincluding sampling weighting bias correction imputation or other methods used to improve representativenessis helpful but not required.

• Experience working with user-level or behavioral data is helpful as is exposure to production data science workflows and tools such as Snowflake AWS Airflow or GitHub.

• Familiarity with AI-powered tools and workflows with an interest in applying emerging technologies to improve productivity learning and outcomes.

• An inclusive and collaborative company culturewe work in an open environment while working together to get things done and adapt to changing needs as they arise.

• A market-competitive total compensation package.

• Volunteer time off and charitable donation matching.

• Strong support for career growth including mentorship programs leadership training access to conferences and employee resource groups.

• A great benefits package including health vision and dental coverage; a Personal Spending Account; unlimited PTO; flexible scheduling; 401(k) matching; travel reimbursement; and more.