Data Scientist

Role overview

The Data Scientist, Corporate joins a core Panel Science team developing mathematically rigorous foundations for enterprise consumer analytics. The work connects statistical modeling, computational infrastructure, and analytical product architecture: refining statistical baselines, improving complex models, and building scalable logic libraries that make consumer insights reliable across product surfaces.

Statistical Foundations and Analytical Infrastructure

• Design, validate, and deploy scalable optimization frameworks and distribution models that preserve mathematical integrity across downstream metrics.
• Explore complex methodologies, evaluate their trade-offs, and implement advanced statistical procedures for panel foundations.
• Partner across functions to turn ad hoc code into standardized, version-controlled templates and reusable logical libraries.
• Structure analytical logic to support products ranging from interactive dashboards to LLM-driven applications.
• Work with Data Engineering to improve code performance and scale analytical workflows, moving complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures.

Quantitative Experience

• Have four to five years of professional data science experience, or two to three years with an advanced degree.
• Hold a bachelor's degree in a highly quantitative discipline such as Statistics, Economics, Physics, Mathematics, Engineering, or a related field.
• Demonstrate exceptional expertise in working with, modeling, and optimizing statistical distributions.
• Use Python or R at an advanced level and SQL at an expert level.

Strongly preferred or advantageous:

• A master's degree.
• Direct experience with panel data or longitudinal consumer data.
• Hands-on analysis of receipt data or transaction-level consumer data.
• Experience using Databricks and scaling advanced compute workloads.

Location, Schedule, and Pay

The role may be performed fully remotely anywhere in the United States, from the New York City headquarters, or from an office hub in Austin, Miami, Denver, Mountain View, or Seattle. East Coast work hours are expected. Depending on where remote work is performed, income may be subject to New York State tax withholding, including when working outside the office locations. Candidates who need visa sponsorship now or in the future cannot be considered.

The published annual on-target earnings are anticipated to be up to $170,000 plus a bonus element. The posting does not identify the currency code or provide a lower bound. This is an OTE statement, not a guaranteed base salary. The final offer may reflect experience, knowledge, skills, abilities, and internal team benchmarks. Equity is also included in the compensation package.

Benefits and Application Details

• Flexible work hours and flexible vacation, alongside the expected East Coast schedule.
• A generous 401(k) match, parental leave, team events, a wellness budget, and learning reimbursement.
• Opportunities to lead meaningful work, build expertise, and grow through demonstrated impact rather than tenure.

Submit a PDF resume to avoid rendering problems. Application questions request relevant project ownership using advanced Python and SQL, quantitative education and data science experience, reasons for seeking the role, employment-gap explanations if applicable, salary expectations, work authorization, and availability. A final hiring step requires arranging reference calls with former managers and others; former direct reports are included for managerial roles. Equal employment opportunity applies, and voluntary demographic responses do not affect hiring decisions. Personal information is handled under the job applicant privacy notice.