Senior Data Scientist, Product Analytics

Senior Data Scientist, Product Analytics Laurel is on a mission to return time. As the leading AI Time platform for professional services firms, we’re transforming how organizations capture, analyze, and optimize their most valuable resource: time. Our proprietary machine learning technology automates work time capture and connects time data to business outcomes, enabling firms to increase profitability, improve client delivery, and make data-driven strategic decisions. We serve many of the world's largest accounting and law firms, including EY, Aprio, Crowell & Moring, and Frost Brown Todd, and process over 1 billion work activities annually that have never been collected and aggregated before Laurel’s AI Time platform. Our team comprises top talent in AI, product development, and engineering—innovative, humble, and forward-thinking professionals committed to redefining productivity in the knowledge economy. We're building solutions that empower workers to deliver twice the value in half the time, giving people more time to be creative and impactful. If you're passionate about transforming how people work and building a lasting company that explores the essence of time itself, we'd love to meet you. About the Role As a Senior Data Scientist, Product Analytics, you will build the analytics foundation that enables Laurel’s Product, Engineering, and Executive teams to make fast, confident, and measurable decisions. You will own the full product analytics lifecycle: defining product success metrics, shaping instrumentation strategies, building canonical datasets, designing core funnels and retention models, and translating findings into clear, actionable direction. You’ll partner closely with Product and Engineering to embed analytics into every release, ensuring Laurel understands what’s working, what isn’t, and why. This is a high-ownership, 0→1 role. You won’t just answer questions. You’ll define the questions, build the frameworks to answer them at scale, and help operationalize Product Analytics as a core capability of the company. You should be deeply analytical, fluent in SQL and Python, and highly comfortable using data to explain behavior, measure impact, and guide product strategy. You are expected to ship production-grade code and contribute to our shared analytics codebase in a thoughtful, maintainable way. This role does not require dedicated ML research responsibilities. However, it is a strong plus if you understand how to evaluate AI/ML models in real-world products. This may include helping define model success metrics, building dashboards that monitor model performance in production, and partnering with the AI team to translate model performance into business impact. What you will do 1. Build Core Product Analytics - Define, standardize, and maintain key product metrics (activation, retention, churn predictors, product feature success criteria, engagement indicators). - Build canonical tables in Laurel’s Analytics Data Warehouse that become the trusted source of truth. 2. Own Feature Measurement & Decision Science - Partner with PMs to define success metrics, guardrails, and experiment decision frameworks before features ship. - Lead meaningful evaluation: “Did the feature actually improve user experience?” 3. Build Funnels, Retention & Behavior Understanding - Develop canonical end-to-end funnels: onboarding → first success → habit formation → retained power usage. - Identify leading indicators of retention and churn. - Uncover insights that drive roadmap prioritization and feature development - Ship actionable dashboards; proactively alert teams when behavior materially changes 4. Raise data quality & instrumentation - Add validation tests and monitoring, triage data issues quickly, and collaborate with Product/Engineering to improve data quality. 5. Help Operationalize the Product Analytics Function - Establish best-practice processes, templates, cadence, and expectations across Produc ... (truncated, view full listing at source)