Snr Prod Analyst 1
1 week ago
Key Responsibilities:
As a member of the Product Analytics team and the larger Product organization, you will be responsible for tracking KPIs, analysing data on consumer journeys and funnels, & sharing actionable insights for the Product teams about the digital customer behaviour and business outcomes on JFL's digital assets. Specific day to day responsibilities will include but will not be limited to:
1. Identify and Track Product KPIs
Identify Product KPIs for defined feature / funnel / experience on the Mobile, Desktop and partner platforms.
Integrate the tracking of the KPI & associated metrics into the development module. Own the end-to-end Implementation & User-Acceptance-Testing of Google Analytics across Android & iOS Apps, Mobile & Desktop websites.
Track each KPI obsessively on a daily basis.
Troubleshoot and debug existing analytics implementation.
Partner with key stakeholders and cross-functional teams to implement and track analytics initiatives across teams; Serve as the point of contact for analytics / tracking requests.
2. Hypothesis generation & validation
Generate hypothesis basis data analysis that is associated with the defined features / experiences.
Identify experiments, research studies and A/B experiments to validate / reject hypothesis. Understand A/B and multivariate testing to be able to implement A/B testing experiments across digital assets.
Derive insights from the hypothesis validation / rejection exercises and share with relevant cross-functional teams.
3. Lead the reporting of actionable insights
Be on top of all user feedback coming through multiple channels, market trends and macro-environment on a regular basis for defined features / experiences.
Assess every step of defined product funnels & identify opportunity to improve conversion across funnels to build great consumer journeys.
Perform structured / adhoc analysis to capture consumer clickstream behavior across all assets.
Crisply and impactfully report on KPIs highlighting insights and pro-actively identify issues / improvement areas for the customer experience and business outcomes. Build reports & automated dashboards to share insights with a myriad of stakeholders.
4. AI-Driven Problem Solving
Use AI/ML tools to enhance productivity and streamline analytical workflows.
Apply AI-driven methods for hypothesis generation, validation, and insight discovery.
Analyze large and complex data sets using AI techniques to surface patterns and opportunities.
5. Product Analytics & App Analytics Tools
Drive deep-dive product analytics to uncover user behavior, funnel performance, and growth opportunities.
Use web and product analytics tools (Mixpanel, Amplitude, Google Analytics, etc.) to generate insights that help shape product strategy.
Conduct detailed A/B test analysis to measure impact, validate hypotheses, and guide product decisions with statistical rigor.
What will you need to succeed in this role?
Excellent problem solving and analytical skills - ability to develop hypotheses, understand and interpret data within the context of the product / business - solve problems and distil data into actionable recommendations.
Strong number crunching and quantitative skills. Intellectual and analytical curiosity – initiative to dig into the why, what & how.
Advanced knowledge of MS Excel and PowerPoint. Ability to write complex SQL queries to pull data from SQL databases.
Expertise in business analytics tools & statistical programming languages. Working knowledge of R or Python to pull data and automate reports.
Strong communication skills with the ability to confidently work with cross-functional teams across the organization and to present information to all levels of the organization.
Inherent interest in the FoodTech, eCommerce and in the consumer Internet & mobile space.
Most importantly, an extremely positive "Can Do" attitude, which continuously drives you to take initiative and demonstrate a high degree of self-motivation.
Strong team player and leadership skills
Qualification:
Bachelors or Masters degree in preferably any of the following: Computer Engineering, Computer Science, Statistics, Mathematics, Data Engineering
Experience:
Previous experience of 3 - 5 years working in an Internet company in a product analytics role. At least 2 years of experience of implementing and working with Google Analytics & Firebase for Apps, Mobile & Desktop Web.
Strong understanding of building and interpreting product funnels in mobile products / apps in a consumer internet setup.
Experience in writing complex SQL queries to pull data from SQL databases.
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