Original listing text, shown exactly as published by the company.
Job Responsibilities
1- Product Performance Partnership
- Serve as the embedded analytics partner for the Product team across every launch, A/B test,
feature tweak, and product modification.
- Define success metrics, target thresholds, and guardrail metrics with PMs before launch — not
after.
- Run pre-launch sizing, post-launch impact reads, and ongoing performance reviews on every
shipped change.
- Proactively surface product opportunities by digging into adoption gaps, friction points, and
behavioral patterns.
2- Experimentation & Causal Inference
- Design and analyze A/B tests, switchbacks, and quasi-experiments. Own the experimentation
rigor bar — sample size, MDE, segment cuts, novelty and network effects.
- Apply best-practice methods (matched pairs, difference-in-differences, regression adjustment)
where randomization is not feasible.
- Communicate results with clear effect sizes, confidence intervals, and recommended decisions
— not just p-values.
3- Tableau Dashboards & Self-Serve Visibility
- Build and maintain the Tableau dashboards that give Product leadership real-time visibility on
every active product, feature, and experiment.
- Design dashboards around the questions PMs actually ask — funnels, cohorts, retention
curves, segment splits — not generic vanity metrics.
- Apply visualization best practices so insights are legible at a glance and decision-ready.
4- SQL & Data Foundations
- Write production-grade SQL against Bosta’s warehouse to extract, transform, and analyze
product event and outcome data.
- Partner with data engineering to ensure clean, reliable instrumentation lands with new
features — not retrofitted weeks later.
- Maintain definitions, metric lineage, and documentation for all product KPIs.
5- Cross-Functional Collaboration
- Partner directly with Product Managers, Designers, and Engineering across the full product
lifecycle — discovery, scoping, launch, iteration.
- Translate ambiguous product questions into analytical workstreams, and analytical findings
into product action.
- Brief leadership on product performance at the right altitude — strategic for execs, tactical for
PMs.
6- Best Practice & Craft
- Bring and embed product analytics best practices — funnels, cohorts, activation, retention,
north-star frameworks, leading vs. lagging indicators.
- Stay current on the product analytics craft (Amplitude, Mixpanel, PostHog patterns, growth
analytics literature) and bring relevant techniques into the team.
- Foster a data-driven culture inside the Product org — equipping PMs to read and reason about
their own data.
Job Requirements
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Job Requirements
- Bachelor’s degree in a relevant field (Data Science, Statistics, Computer Science, Economics, Engineering, or similar).
- 4–6 years of analytics experience, with at least 2–3 years specifically in product analytics, partnering directly with Product teams.
- Demonstrated track record across full product launch cycles — pre-launch design, instrumentation, A/B testing, post-launch impact reads.
- Strong proficiency in SQL — able to write complex, performant queries against production warehouses independently.
- Hands-on Tableau experience building and maintaining dashboards for non-technical product audiences. (Power BI / Looker considered if Tableau ramp-up is fast.)
- Solid grounding in experimentation methodology and product analytics best practices (funnels, cohorts, retention, north-star metrics).
- Python proficiency for analysis, automation, and statistical work.
- Strong business acumen and the ability to translate product questions into rigorous analytical solutions — and analytical results back into clear product recommendations.
- Tech startup/marketplace / logistics-product experience is a strong plus.
- Excellent stakeholder communication — equally comfortable with PMs, engineers, and execs.
