Job Category

Marketing & Communications

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place Agentforce is the future of AI, and you are the future of Salesforce.

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.

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 reportabl

📌 Trailhead | Sr Data Analyst/ Data Scientist (Ciudad de México)
🏢 Salesforce
📍 Ciudad de México