Data Scientist

About the role

Company Overview

Be a part of a fast-growing, winning team helping Fortune 1000 consumer brands and retailers leverage AI-driven data insights.

OpenBrand is one of the world’s most respected market intelligence companies. OpenBrand’s data and market research products give manufacturers, retailers, and industry players a competitive edge across a wide range of industries (including IT, consumer electronics, home appliances, health, wellness, beauty, small appliances, and other consumer durables) and help marketing, product, sales, and pricing teams make more informed decisions in a rapidly changing market environment.

Role Overview

This role is a hands-on Data Scientist focused on building, scaling, and maintaining production-grade market insight, market share, media spend estimation, and channel sizing products powered by alternative datasets such as email receipts, clickstream, credit card transaction data, ad/media signals, and external benchmarks.

You will work at the intersection of modeling, data engineering, and operational excellence, with a strong emphasis on:

Designing and maintaining efficient, reliable data pipelines

Implementing robust QA and monitoring processes

Ensuring consistent, explainable, and client-ready outputs

While strong modeling and statistical skills are essential, this role is less R&D-focused and more execution- and delivery-oriented, with ownership over how models and methodologies perform in production over time.

You will collaborate closely with Engineering, Product, and Operations teams to operationalize methodologies, improve data quality, and support ongoing product evolution. This role does not focus on people management, but requires strong judgment, independence, and end-to-end ownership.

Key Responsibilities

Data Products & Modeling

Design, build, and maintain models and analyses that transform alternative data sources (e.g., receipts, clickstream, credit card data) into market share, sales, and competitive insight metrics

Build and validate media spend estimation methodologies that combine observed signals, coverage assumptions, calibration factors, external benchmarks, and uncertainty ranges

Develop channel sizing models that estimate market, brand, retailer, category, and media-channel opportunity from incomplete or biased source data

Translate noisy source signals, such as ad occurrences, receipts, transaction records, clickstream events, panel data, and vendor feeds, into explainable spend, share, and channel-size outputs

Develop and maintain projection, normalization, and estimation methodologies suitable for production use

Combine overlapping and complementary data sources into coherent, scalable estimation frameworks

Develop new analyses and support ongoing model iteration with a strong focus on stability, explainability, and consistency

Data Pipelines & Quality

Partner with Engineering to design and maintain efficient, scalable data pipelines from raw ingestion through client-facing outputs

Define and implement data quality checks, validation rules, and monitoring across the pipeline

Investigate and resolve data anomalies, breaks, or regressions in collaboration with Ops and Engineering

Own the scientific and methodological integrity of production outputs, including documentation and change management

Operational Excellence & Cross-Functional Collaboration

Work closely with Operations teams to ensure smooth ongoing production and delivery of insights

Support Product teams with methodological input for roadmap decisions, client questions, and product enhancements

Perform ad-hoc and exploratory analyses to support client inquiries, data investigations, and internal decision-making

Help establish best practices for reproducibility, QA, and operational handoff of data science work

Qualifications

Education & Experience

5+ years of experience in a Data Science or related analytical role, with significant hands-on responsibility for production data products, analytical models, or decision-support insights

BS or MS degree in a highly analytical field (e.g., Mathematics, Statistics, Physics, Computer Science, Engineering)

Technical Skills

Strong statistical, quantitative, and analytical skills, with experience building and maintaining models in production

Experience with projection, calibration, sampling-bias correction, benchmark reconciliation, and uncertainty quantification for estimation products

Advanced proficiency in Python (pandas, NumPy, scikit-learn or similar)

Strong SQL skills and experience working with large-scale analytical datasets

Experience using Large Language Models (LLMs) (e.g., GPT-based or similar) to improve productivity and efficiency in data science workflows, including tasks such as data exploration, code development, documentation, QA investigation, and analysis support.

Experience designing workflows that are robust, testable, and maintainable over time

Comfort working across the full lifecycle: raw data → modeling → QA → delivery

Preferred Experience

Experience working with alternative datasets, including:

Email or digital receipt data

Clickstream, behavioral, or web-scraped data

Credit card or transaction-level data

Experience building or maintaining Market Share, Market Insights, or Sales Measurement products

Experience with media spend estimation, channel sizing, market sizing, media measurement, or ad intelligence products, including familiarity with CPM, rate cards, campaign measurement, and share-of-voice analysis

Experience correcting for panel coverage, sampling bias, sparse observations, missing channels, and external benchmark calibration

Domain experience in Consumer Durables, Retail Financial Services and/or CPG

Experience collaborating closely with Engineering and Ops teams on production pipelines

Familiarity with cloud-based data platforms and distributed processing (e.g., Snowflake, Spark, AWS)

Pay & Benefits Summary

Medical, Dental, Vision, and Life Insurance

Flexible Spending Account (FSA) and Health Reimbursement Arrangement (HRA)

401(k) Retirement Plan with Company Matching

Flexible Time Off

Paid Parental Leave

Base salary range: $150,000-$200,000 annually

This role is also eligible for an annual discretionary performance bonus, subject to the terms of the applicable bonus plan