Data Scientist

Data ScientistLocation: Remote, USA or Hybrid (Louisville, KY or San Diego, CA)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 OverviewThis 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 pipelinesImplementing robust QA and monitoring processesEnsuring consistent, explainable, and client-ready outputsWhile 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 ResponsibilitiesData Products & ModelingDesign, 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 metricsBuild and validate media spend estimation methodologies that combine observed signals, coverage assumptions, calibration factors, external benchmarks, and uncertainty rangesDevelop channel sizing models that estimate market, brand, retailer, category, and media-channel opportunity from incomplete or biased source dataTranslate noisy source signals, such as ad occurrences, receipts, transaction records, clickstream events, panel data, and vendor feeds, into explainable spend, share, and channel-size outputsDevelop and maintain projection, normalization, and estimation methodologies suitable for production useCombine overlapping and complementary data sources into coherent, scalable estimation frameworksDevelop new analyses and support ongoing model iteration with a strong focus on stability, explainability, and consistencyData Pipelines & QualityPartner with Engineering to design and maintain efficient, scalable data pipelines from raw ingestion through client-facing outputsDefine and implement data quality checks, validation rules, and monitoring across the pipelineInvestigate and resolve data anomalies, breaks, or regressions in collaboration with Ops and EngineeringOwn the scientific and methodological integrity of production outputs, including documentation and change managementOperational Excellence & Cross-Functional CollaborationWork closely with Operations teams to ensure smooth ongoing production and delivery of insightsSupport Product teams with methodological input for roadmap decisions, client questions, and product enhancementsPerform ad-hoc and exploratory analyses to support client inquiries, data investigations, and internal decision-makingHelp establish best practices for reproducibility, QA, and operational handoff of data science workQualificationsEducation & Experience5+ 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 insightsBS or MS degree in a highly analytical field (e.g., Mathematics, Statistics, Physics, Computer Science, Engineering)Technical SkillsStrong statistical, quantitative, and analytical skills, with experience building and maintaining models in productionExperience with projection, calibration, sampling-bias correction, benchmark reconciliation, and uncertainty quantification for estimation productsAdvanced proficiency in Python (pandas, NumPy, scikit-learn or similar)Strong SQL skills and experience working with large-scale analytical datasetsExperience 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 timeComfort working across the full lifecycle: raw data ? modeling ? QA ? deliveryPreferred ExperienceExperience working with alternative datasets, including:Email or digital receipt dataClickstream, behavioral, or web-scraped dataCredit card or transaction-level dataExperience building or maintaining Market Share, Market Insights, or Sales Measurement productsExperience 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 analysisExperience correcting for panel coverage, sampling bias, sparse observations, missing channels, and external benchmark calibrationDomain experience in Consumer Durables, Retail Financial Services and/or CPGExperience collaborating closely with Engineering and Ops teams on production pipelinesFamiliarity with cloud-based data platforms and distributed processing (e.g., Snowflake, Spark, AWS)Benefits SummaryMedical, Dental, Vision, and Life InsuranceFlexible Spending Account (FSA) and Health Reimbursement Arrangement (HRA)401(k) Retirement Plan with Company MatchingFlexible Time OffPaid Parental Leave