We are seeking a self-motivated, architect-minded Senior Data Scientist & Analytics Engineer to own our data insights pipeline and analytical framework. Our core product experience relies heavily on algorithmic accuracy, making data pipeline integrity and precise event-driven telemetry mission-critical.

In this role, you will bridge the gap between product infrastructure and business insights. You will not just build dashboards; you will design the data models, ensure upstream pipeline accuracy, run predictive simulations, and optimize the discovery algorithms that drive our platform. The ideal candidate is platform-agnostic but deeply opinionated about building clean, reproducible, and scalable data pipelines.

• Pipeline Integrity & Modeling: Own the analytical data layers and transformation pipelines (e.g., dbt) that feed our product. Ensure that upstream event telemetry is clean, reliable, and perfectly modeled for consumption.

• Algorithmic Refinement: Partner closely with Engineering and Product teams to validate, iterate, and optimize our ranking and recommendation systems.

• Behavioral Simulations: Build and run predictive user-experience simulations and cohort analyses to understand platform stickiness, feature adoption, and user journeys.

• Catalog Architecture: Advise on best practices for our extensive asset catalog metadata (creators, content, and taxonomies), ensuring data structures support optimal discovery and search performance.

• Data Aggregation: Build and maintain the ingestion pathways to normalize disparate marketing, ad platform, and web attribution sources.

• Unified Attribution: Map top-of-funnel acquisition data directly to on-platform behavioral data, giving the business an accurate, unified view of LTV, CAC, and campaign effectiveness.

• Modern BI Infrastructure: Move the business away from our current reporting tools by establishing a robust, scalable analytics layer that serves as the single source of truth.

• Web & Event Telemetry: Standardize clickstream and session tracking across the platform, ensuring clean event schemas and dependable data layers.

Experience: 5+ years of experience in an analytical engineering, data science, or pipeline-heavy product analytics role. Experience within a high-growth B2C digital platform, streaming service, or digital marketplace is a significant advantage.

Pipeline Expertise: Deep experience designing, testing, and maintaining analytics pipelines. Strong opinions on data warehousing architecture, schema-on-write vs. schema-on-read, and data quality enforcement.

• Advanced, production-grade SQL and experience with modern transformation frameworks (e.g., dbt).

• Proficiency in Python or R for statistical modeling, simulations, and data engineering tasks.

• Hands-on experience with event-driven telemetry frameworks.

Domain Knowledge: A strong understanding of digital media services, content discovery engines, or heavy catalog metadata systems is highly desirable.

Communication: The ability to speak the language of infrastructure engineers when discussing data pipelines, while seamlessly translating complex data anomalies into strategic insights for business leaders.

• The autonomy to design and own the data analytics infrastructure of a rapidly evolving digital platform from the ground up.

• A high-impact environment working alongside a seasoned engineering and leadership teams.

To apply, send your resume to careers@thehiddenjams.org and tell us why you think you'd be a good fit.