Trailhead | Sr Data Analyst/ Data Scientist

About Trailhead

Trailhead is Salesforce's free online learning platform and the front door to the Salesforce ecosystem. It empowers anyone to build in-demand skills across AI, Agentforce, CRM, data, and business fundamentals, and helps organizations re-skill their workforce for the agentic era. Today, Trailhead is also an AI-powered learning experience, with personalized pathways and the Trailhead Learning Agent guiding learners every step of the way.

The Trailhead Content team generates ideas, writes and edits content, develops hands‑on challenges, and publishes and maintains the learning content that makes all of this possible. We believe content should be accessible, educational, relevant, and enjoyable. Right now, we're building some of the most important learning content in the Salesforce ecosystem. This is your chance to be part of it.

Role Description

As Senior Data Analyst, you are a senior lead and expert on the team across three connected facets of Trailhead measurement: content analytics and performance (the Content Intelligence Engine — catalog health, portfolio performance, journey tracking), learner satisfaction and feedback (structured survey data — CSAT, confidence gain, qualitative themes), and business impact (whether Trailhead engagement moves Pipeline Generation, Deal Velocity & Win Rate, and Product Adoption). You build the semantic models, data pipelines, and predictive frameworks that turn structured and unstructured signals into decisions — for content owners, executives, and increasingly, AI agents.

Your Impact

• Content analytics and performance: Own the Content Intelligence Engine's core metrics and portfolio views (catalog-level completions, L1 product performance, content health vs. performance, journey drop‑off) and lead its evolution from MVP through fast‑follows and V2 capability.
• Learner satisfaction and feedback: Design how unstructured/qualitative learner feedback (open-text survey responses, confidence pre/post scores) is captured, structured, and made analyzable at catalog scale — building the pipeline from raw survey response to reportable CSAT/confidence-gain metrics and automated qualitative theme surfacing for content owners.
• Business impact: Own cohort design and methodology (propensity/segment matching) connecting Trailhead engagement signals (TBIDs, badges, Agentblazer status) to commercial outcomes (NNAOV, Win Rate Lift, Time‑to‑Close, Account Penetration), with defensible bias controls, not just directional correlation.
• Architect and own a living semantic model of content performance spanning all three facets — shared metric and cohort definitions that persist and adapt as the Trailhead catalog, survey infrastructure, and AI tooling evolve, rather than one-off analyses that go stale.
• Structure both structured (engagement, business) and unstructured (survey/qualitative) data to be agent‑queryable — usable by AI layers to reason directly over content quality, learner sentiment, and business outcome questions, not just populate a static dashboard.
• Own the logic and definitions that connect learner identity data to business/sales records, content completions to sales opportunities, and survey responses to the specific content they reference
• Lead the platform strategy for dashboards and models — keeping pace with Salesforce's evolving analytics and approved AI tooling — and lead the build of the underlying semantic model as our platform evolves.
• Translate findings across all three facets into a single, clear narrative for content owners, Trailhead leadership, Marketing, Product, Sales and Customer Success leadership — distinguishing high‑confidence findings from directional ones.

Required Skills & Experience

• 5+ years in data analytics or data science, spanning both structured (SQL/engagement/CRM) and unstructured (qualitative/text/survey) data analysis — this is a genuinely three‑sided role, not a single‑discipline one.
• Comfort applying data science methods (cohort/propensity matching, predictive modeling, causal inference) to answer \"does this actually work\" questions, not just descriptive reporting.
• Advanced SQL experience querying large‑scale cloud data warehouses (e.g. Snowflake), including learner activity data and sales/CRM data (opportunities, order line items, contracts).
• Experience structuring and analyzing unstructured/qualitative data — open‑text survey responses, sentiment/theme extraction — turning free text into reportable, comparable signal.
• Working knowledge of cohort/propensity‑matching methodology for business impact analysis.
• Expert Tableau dashboard‑building, with strong data visualization and design sense; hands‑on experience using AI‑assisted development