Data Analyst - 2

Bengaluru · Full Time · On-Site. Work closely with Product Managers to provide data-driven inputs on product performance, user behaviour, and growth… organization serving the digitally-savvy, ACKO’s value proposition of ‘Welcome Change’ focuses on offerings that make insurance simple and hassle-free! With features such as zero commission, zero paperwork, instant renewal, same-day claim settlements, and app-based updates on claims, ACKO is a 'Welcome Change' from traditional insurers. Having said that, we are not just another conventional insurance firm, or the people consulted solely for "claims”! Anchored in a tech-centric philosophy, ACKO’s approach fuels innovation, empowering us to develop comprehensive products that cater to every aspect of our customers' insurance requirements. And while we are at it, we put our Ackers at the heart of everything we do. We're not your typical 9-to-5 workplace; we're a vibrant and inclusive bunch of innovators and creators making sure every Acker’s idea matters, their voice is heard, and their growth is part of our mission. Roles and RESPONSIBILITIES: Work closely with Product Managers to provide data-driven inputs on product performance, user behaviour, and growth opportunities - translating findings into clear, actionable recommendations. Analyse product funnels, cohorts, trends, LTV, DAU/MAU, retention, and user behavior to support prioritisation and decision-making. Define and own stakeholder requirements for customer usage metrics, KPIs, and reporting processes; build and maintain dashboards and reports that surface meaningful signals. Obsessively study customer usage data to proactively identify opportunities for driving higher engagement, improved retention, product improvements, and monetisation levers. Design experiments and analyse A/B tests to measure feature impact and inform product decisions. Design and maintain data marts, dimensional models, and semantic layers that enable self-serve analytics across product and business teams; enforce schema standards and documentation practices. Leverage AI tools effectively and responsibly in day-to-day analytical workflows for better efficiency and maintaining accuracy standards before sharing results with stakeholders. Coordinate independently with cross-functional teams (Product, Engineering, Marketing, Business) and drive fast-paced execution with accountability. QUALIFICATIONS: B.Tech/BE from a premier institute (IITs/BITS/NITs or equivalent). 3–5 years of relevant experience in Product Analytics or Business Analytics, preferably within a consumer internet / product-tech B2C company (fintech, e-commerce, online marketplaces, etc.). Prior experience working with high-scale consumer products and large user behaviour datasets is a strong advantage. Skills Required: Product Analytics & BI Tools: Hands-on experience with Amplitude (or similar product analytics platforms such as Mixpanel) for event-level analysis, funnel tracking, and behavioral segmentation. Proficiency with Power BI or equivalent BI tools for dashboard development. Experimentation & A/B Testing: Practical experience designing, running, and interpreting A/B tests and product experiments - understanding test setup, success metrics, statistical significance, and translating results into recommendations. SQL & Python: Strong SQL skills for complex querying, aggregation, and data transformation. Python proficiency for data wrangling, analysis, and automation (pandas, Num Py). Data Modelling & Schema Design: Working knowledge of data warehouse concepts - star/snowflake schemas, data marts and dimensional modelling. Ability to work with data engineering teams to define schemas and ensure analytical reliability. AI-Augmented Workflows: Demonstrated ability to use AI tools accurately and efficiently in analytical work - including validating AI outputs, spotting hallucinations, and maintaining rigorous standards before sharing results. Excel: Strong MS Excel skills for ad hoc analysis and stakeholder-facing deliverables. Excellent problem-solving skills, strong oral and written communication, and the ability to present complex data clearly to non-technical audiences. Self-motivated, personally accountable, and comfortable working under pressure in a dynamic environment. Good to Have: Understanding of Machine Learning concepts (classification, regression, clustering, propensity modelling) and ability to collaborate with or interpret outputs from data science teams. Apply for this position Autofill from resume Save time by uploading your resume. (Only PDF or DOCX format supported) Upload file Loading...