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Source · 1 day ago

Product Data Scientist (Multiple Levels)

United States

Full-time

Remote

Mid, Senior Level

$169K/yr - $224K/yr

3+ years exp

Source is redefining how the built world comes together by building an AI-native platform for global commercial construction. The Product Data Scientist role focuses on building and maintaining core analytics, enabling product insights, and evolving into deeper data science work as the company matures.

ArchitectureConstructionDatabaseMarketplaceProcurementSaaS

No H1B

Responsibilities

Design, build, and maintain scalable ETL / ELT pipelines that power product analytics and reporting

Partner with Product and Engineering to define and implement instrumentation, logging, and telemetry for new features

Define, document, and maintain core product metrics and dashboards; ensure data quality, reliability, and consistency

Conduct exploratory, diagnostic, and descriptive analyses to answer product and business questions

Contribute to applied modeling efforts (e.g., recommendation, ranking, scoring, or forecasting systems) in collaboration with engineering partners

Partner with Product and Business stakeholders to frame hypotheses, evaluate trade-offs, and guide roadmap and investment decisions

Support the design, execution, and analysis of experiments as experimentation capabilities develop

Apply causal inference and predictive techniques to assess impact and inform strategy

Thoughtfully evaluate where AI or automation can meaningfully improve product insights, internal workflows, or customer-facing experiences

Continuously improve the performance, reliability, and scalability of analytics pipelines and data models

Contribute to data standards, documentation, and best practices as the data function grows

Help shape tools and processes that enable the broader organization to use data effectively

Qualification

SQLPythonProduct analyticsApplied modelingData qualityCommunication skillsCollaborationProblem-solving

Required

Advanced degree or equivalent practical experience in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field

3+ years of experience in product analytics, applied data science, analytics engineering, or related roles

Strong experience working with large, event-level datasets and building analytics-ready data models

Proficiency in SQL and at least one analytics or programming language (e.g., Python)

Experience defining product metrics, building dashboards, and supporting self-serve analytics

Ability to independently own ambiguous problems end-to-end—from data reliability to insight to action

Strong communication skills and comfort collaborating with Product, Engineering, and Business partners

Preferred

Familiarity with AI-assisted tools or workflows that augment analysis, exploration, automation, or decision-making

Experience contributing to applied modeling efforts such as: recommendation or ranking systems (e.g., discovery, relevance, prioritization), scoring models (e.g., risk, reputation, quality, or trust), forecasting or propensity models used for planning or strategy

Experience supporting experimentation, causal inference, or impact measurement in a product environment

Product analytics experience in consumer, marketplace, SaaS, or platform products

Experience working in early-stage or fast-evolving environments