Senior Data Analyst – Lifecycle & Retention DataNest | Full-time | Remote within India; Bengaluru preferred Ideally 3–5 years of relevant experience U.
S. Eastern time alignment required, with an approximate collaboration window of 8 a.m.–6 p.m. Eastern. Exact shift and overlap requirements will be discussed during hiring. ABOUT DATANEST DataNest is a data and analytics practice focused on reliable data foundations, practical business insight, and close collaboration with business teams. THE ROLE Own lifecycle and retention analytics within an ongoing business engagement, working directly with U.
S.-based stakeholders in a fast-moving startup environment. Analyse customer behaviour across web and mobile app experiences in a SaaS and subscription business environment. Connect onboarding, activation, engagement, renewal, and reactivation to sustainable customer value. This is a hands-on role with scope to guide one or two analysts. We need a fast learner who brings structure to ambiguous problems, takes initiative, and becomes a trusted business partner with limited supervision. WHAT YOU WILL OWN
• Define lifecycle metrics for activation, repeat purchase, engagement, retention, churn, reactivation, and customer lifetime value, with clear populations, denominators, cohorts, and measurement windows.
• Diagnose performance changes, distinguish business drivers from data issues, and recommend actions across customer segments and journey stages.
• Partner with lifecycle, marketing, product, and operations stakeholders to challenge assumptions, prioritise opportunities, and turn findings into decisions.
• Establish agreed metric definitions, document business logic, and embed consistent metrics into planning and performance reviews.
• Design and analyse experiments: define hypotheses, success metrics, guardrails, eligibility, randomization units, sample sizes, and measurement plans. Evaluate lift, uncertainty,



practical significance, and incrementality; investigate sample-ratio mismatches and tracking issues.
• Analyse web and app funnels, onboarding, feature adoption, conversion, and renewal. Help define event taxonomies and validate tracking across frontend and backend systems.
• Measure SaaS and subscription performance, including trial-to-paid conversion, customer and revenue retention, renewals, expansion, and contraction.
• Build reusable analytical datasets in SQL and dbt. Define grain, keys, relationships, fact and dimension tables, historical changes, and business logic; prevent duplicate records and incorrect joins. Add tests, documentation, and version control.
• Build trusted dashboards and self-service reporting; automate recurring work and maintain scheduled workflows, dependencies, and refreshes using tools such as Airflow or Dagster.
• Maintain a record of experiment designs, results, and decisions so teams build on prior learning.
• Scope work, review SQL and analyses, and mentor one or two analysts while maintaining high standards of accuracy and communication. WHAT YOU BRING
• Ideally 3–5 years in data, product, growth, or business intelligence analytics. Demonstrated ownership and judgment matter more than an exact year count.
• Strong SQL, including complex joins, window functions, cohort analysis, data modelling, debugging, query performance, and validation.
• Hands-on dbt experience building modular, tested, documented analytical models using Git.




• Practical lifecycle, retention, churn, or repeat-purchase analysis experience, preferably in SaaS, subscriptions, consumer products, or e-commerce.
• Experience designing and analysing A/B tests; understanding of power, sample size, confidence intervals, correlation versus causation, and common interpretation pitfalls.
• Experience with web or mobile event data, funnels, instrumentation, and customer journeys; ability to learn the other platform quickly.
• Experience with a contemporary platform such as Snowflake or Databricks, and familiarity with AWS or comparable cloud environments.
• Experience with Domo, Looker, Mode Analytics, Hex, or comparable BI and analytical tools; expertise in every listed tool is not required.
• Working knowledge of Airflow, Dagster, or similar orchestration tools, including scheduled jobs, dependencies, and failed-job investigation.
• Excellent written and spoken English and confidence presenting recommendations to U.
S.-based stakeholders.
• Ability to learn quickly, manage changing priorities, flag risks early, and independently follow work through to completion.
• Experience mentoring analysts or leading an analytical project or business area.
• Based in India and authorized to work in India; Bengaluru preferred. Ability to align with U.
S. Eastern

working hours
is required. NICE TO HAVE Python for analysis, automation, or statistical work; CRM and lifecycle messaging analytics; experience in a small, rapidly evolving team. SUCCESS IN YOUR FIRST THREE MONTHS Develop a solid understanding of the customer lifecycle and data, establish trusted retention metrics, independently deliver analyses and experiments that inform decisions, and provide clear guidance to junior analysts. Your area should move forward reliably without constant direction.

📌 Senior Data Analyst – Lifecycle (India)
🏢 DataNest
📍 India