CX Analyst & Product Insights

Role & Responsibilities We’re building a central Design Thinking function at Bajaj Finance - a team that will play a defining role as the organisation pivots into a direct-to-consumer company. This role sits at the intersection of data and human understanding, and thrives in that grey zone. You’ll be the person who can stare at a funnel and see a human story. Who can sit with a field research readout and spot what’s missing. Who treats data not as an answer, but as a better question - and turns both into something the team can act on.

What Your Work Looks Like- You’ll operate across the Design Thinking lifecycle — from signal to solution:

• Insight & Evidence: Journey analytics, Mining session replays, heatmaps, and behavioural data to surface where customers struggle and why. You bring statistical rigour — you know the difference between a pattern and noise, between correlation and causation, and you know when to trust the data and when to trust instinct.
• Challenge & Synthesis: You consume field research from dedicated research teams and stress-test it. You triangulate digital signals against qualitative findings, competitive benchmarks, and business metrics to build problem statements that hold up under scrutiny. You craft How Might We statements from clustered signals — framing the right questions that give the team a clear direction to solve against.
• Prototyping & Testing: You participate in solutioning — helping the team move from problem to prototype, designing tests, and closing the loop between what was hypothesised and what customers actually do.

What Makes Someone Right For This-

• 4–8 years in consumer insights, CX analytics, product analytics, UX research, or a similar role in B2C or consumer-facing companies, where you’ve worked across quantitative and qualitative inputs
• Comfortable in analytics platforms — session replay, web/app analytics, funnel analysis, segmented and cohort analysis. Can layer behavioural data over system-of-record data to move beyond surface-level insights. Specific tools matter less than your ability to get depth from any tool quickly
• Understands statistical thinking — hypothesis testing, significance, when to apply rigour and when to move on intuition
• Can read, challenge, and build on qualitative research even if you’re not the one conducting it — you know what good methodology looks like and can spot when a finding is thin
• Structures findings into clear, concise arguments. You’ve presented to senior stakeholders and know the difference between showing data and making a case
• Thinks in systems — you connect a drop-off at step 3 to an upstream design choice, a policy constraint, and a downstream business metric without being told to
• SQL-literate — you can pull what you need or speak to data teams in their language
• Brings critical reasoning that stress-tests assumptions rather than confirming them Ideal Candidate
• Strong Consumer Insights / CX Analytics / Product Insights profile (behavioral/user/product/UX analytics)
• Mandatory (Experience 1) - Must have 4+ years of experience in Customer Experience (CX) Analytics, Consumer Insights, Product Analytics, Behavioral Analytics, or UX Analytics, working on B2C digital products (Web/App) with a focus on understanding customer behavior, customer journeys, and experience improvement.
• Mandatory (Experience 2) - Must have hands-on experience analyzing customer journeys, behavioral funnels, digital interactions, session-level behavior, clickstream data, and experience metrics to identify pain points, drop-offs, and optimization opportunities.
• Mandatory (Experience 3) - Must have experience using CX and Digital Experience Analytics platforms such as Medallia, ContentSquare, Google Analytics (GA4) or similar tools for customer behavior analysis, journey mapping, and insight generation.
• Mandatory (Experience 4) - Must have experience working closely with Product, Design, CX, Business, Marketing, and Research teams to generate insights, validate hypotheses, and drive customer experience improvements.
• Mandatory (Experience 5 ) - Strong working knowledge of SQL and Python for data extraction, querying, analysis, exploratory data analysis, automation, and behavioral data interpretation. Ability to independently analyze large datasets, identify patterns, and generate actionable business insights.
• Mandatory (Experience 6): Understanding of hypothesis-driven thinking and basic experimentation/A/B testing concepts, including interpreting results and distinguishing between correlation and causation.
• Preferred ( Experience 1) - Candidates from product-based companies (B2C preferred) OR Data Analytics Service companies like Mu Sigma etc Skills: customer,data,research,design,cx,analytics,b2c