Senior Product Data Analyst

At speedapp, we are a team of IT experts and other professionals working for clients worldwide, including Israel, Austria, and the USA. We have 10 years of experience, serve over 100 clients globally, and make more than 300 hires per year. We have been awarded the "Forbes Diamonds" four times and are recognized among the fastest growing companies by Clutch.

• 5+ years of experience in product, marketing, or business data analysis.
• Strong SQL skills for querying and aggregating warehouse data.
• Hands-on experience with Tableau or Power BI as a user, including published data sources and aggregated reporting.
• Hands-on experience with Mixpanel or Amplitude, including events, funnels, cohorts, and experiment properties.
• Practical experience in A/B test analysis with hypothesis framing, sample checks, and segmented readouts.
• Experience with multi-market B2C consumer products.
• High level of English proficiency, both written and verbal.

Nice to have:

• Travel or e-commerce domain experience.
• Comfortable using AI tools for data querying and analysis.
• Experience with Google Analytics.
• Experience with session replay or UX analytics tools such as Microsoft Clarity.
• Experience with Python or R for one-off analysis scripts.

• Partner with Product on weekly questions regarding funnel conversion, campaign health, experiment outcomes, and user drop-offs.
• Support price accuracy and metasearch performance by analyzing patterns, quantifying impact, and tracking trends collaboratively with engineering and platform teams.
• Own Mixpanel data quality by validating events, maintaining dashboards, and identifying tracking gaps.
• Design and interpret A/B tests, including sample balance checks, segmentation, and providing clear recommendations with stated confidence and caveats.
• Use and maintain operational reporting in BI tools related to bookings, revenue, marketing performance, and funnel health.
• Communicate findings clearly to Product, stakeholders, and leadership, including cases where data is insufficient to support decisions.