Senior Data Scientist and Analytics Engineer

Careers: Senior Data Scientist and Analytics Engineer 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. Key Responsibilities Pipeline Architecture & Core Data Science 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. Growth & Marketing Data Integration 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. Business Intelligence & Telemetry 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. Qualifications & Technical Profile 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. Core Technical Skills: 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. What We Offer 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. #J-18808-Ljbffr