Data Scientist

OpenBrand; Chicago (IL); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Health insurance

Dental & Vision

401(k) with match

Flexible time off

Job summary

OpenBrand is seeking a Data Scientist in Chicago (hybrid, remote available) to build production-grade market insight and channel sizing products using alternative data sources. You will design data pipelines, implement QA, and deliver explainable outputs for clients, collaborating with Eng, Product, and Ops teams to scale and improve models in production.

You will combine modeling, data engineering, and operations to ensure stable, auditable results, with 5+ years in the field and a strong

Qualifications

• 5+ years in Data Science with production data products or decision-support insights.
• BS or MS in Mathematics, Statistics, Physics, CS or Engineering.
• Experience building scalable data products and production-ready workflows.

Responsibilities

• Design, build, and maintain production-grade data models and analyses from alternative data sources.
• Develop and validate media spend estimation methodologies with external benchmarks.
• Create channel sizing models for market, brand, retailer, and media analyses.
• Translate signals into explainable spend, share, and channel outputs for clients.
• Partner with Engineering to build robust, scalable data pipelines and QA checks.
• Own data quality, validation, and documentation across production outputs.

Skills

Python

SQL

Production models

LLMs

Data pipelines

Education

BS or MS in a highly analytical field

Tools

Snowflake

Spark

AWS

Job description

Location: Chicago (hybrid) preferred, remote available

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
• 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
• 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