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Bangalore, Karnātaka, India
Actively hiring, first seen by us 2 days agoOwn the product analytics framework for the expert platform
Define outcome metrics for matching and tooling decisions
Size initiatives with impact estimates before they are built
Design and run the experimentation program, including switchback and cluster-randomized tests
Track every launch after it ships and catch regressions
Own the product analytics framework for the expert platform
Define the outcome metrics that make matching and tooling decisions comparable
Size initiatives before they are built
Design and run the experimentation program, including the designs this domain requires: switchback, cluster-randomized, and interference-aware tests
Track every launch after it ships: confirm the sized impact actually materialized, monitor it over time, and catch regressions before the business feels them.
7+ years of analytics and data science experience, with meaningful depth in product analytics for a software or AI product.
Experience leading and developing analysts and/or data scientists while continuing to contribute hands-on.
Experience sizing opportunities to prioritize a product roadmap
Experience measuring AI, search, recommendation, or retrieval-based systems beyond accuracy alone.
Experience defining event instrumentation from scratch and driving it through an engineering roadmap.
Proficient with SQL and Python; experience applying AI and generative AI tooling to accelerate analysis.
- Outstanding communication with technical and non-technical audiences, able to make a crisp recommendation under uncertainty. - Bachelor's or Master's degree in a quantitative field. Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
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Day 2
Early. Similar jobs usually come down between day 7 and day 54.
At Intuit, jobs usually come down by about day 22.
From 7,937 similar postings that came down, and 64 of Intuit’s. Coming down is not always a hire.
59 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Experience defining event instrumentation from scratch and driving it through an engineering roadmap. - Proficient with SQL and Python; experience applying AI and generative AI tooling to accelerate analysis. - Outstanding communication with technical and non-technical audiences, able to make a crisp recommendation under uncertainty.
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
The Intuit Customer Success (ICS) Data Science & Analytics team is seeking a Manager 2, Data Science to lead product analytics for the platform that connects customers with our experts: how customers are routed and matched to the right expert, and how the knowledge and AI-powered tools experts use shape the outcome.
This is a player-coach role. You will lead a small team of analysts and data scientists while spending a material part of your time staying hands-on in the data yourself, and you will be the analytics voice in the room with product managers and product development leaders, defining what 'good' looks like before a feature ships and what evidence a change must produce to earn a rollout.
Responsibilities
Own the product analytics framework for the expert platform (event taxonomy, instrumentation requirements, adoption and funnel measurement), spanning how customers are matched to experts and how experts use the knowledge and AI tools available to them.
Define the outcome metrics that make matching and tooling decisions comparable: time to connect, first-contact resolution, transfer and re-contact rate, satisfaction, conversion, and expert efficiency.
Size initiatives before they are built; turning product problem statements into measurable impact estimates from behavioral data, separating total from achievable opportunity, and using those estimates to stack-rank the roadmap with product partners.
Design and run the experimentation program, including the designs this domain requires: switchback, cluster-randomized, and interference-aware tests where routing one customer changes what is available to the next.
Apply causal inference (difference-in-differences, propensity score, synthetic control, instrumental variables) to isolate product impact from shifts in demand mix, staffing, and seasonality.
Track every launch after it ships: confirm the sized impact actually materialized, monitor it over time, and catch regressions before the business feels them.
Evaluate AI-driven experiences, including matching and ranking models as well as retrieval and knowledge tools, against both offline quality benchmarks and online behavioral outcomes.
Partner directly with product managers, product development leaders, and engineering on roadmap, launch readiness, and post-launch learning, as an equal voice rather than a reporting function.
Drive data enablement for the domain: gap assessments, instrumentation requirements handed to engineering, metric definitions, data quality monitoring, and self-serve reporting.
Set the technical bar for the team, review work in detail, and coach on both method and business framing.
Qualifications
7+ years of analytics and data science experience, with meaningful depth in product analytics for a software or AI product.
Experience leading and developing analysts and/or data scientists while continuing to contribute hands-on.
Demonstrated partnership with product management and engineering leaders through a full product lifecycle: discovery, launch, evaluation, and iteration.
Experience sizing opportunities to prioritize a product roadmap
Hands-on experimentation design and analysis, including guardrail metrics, variance reduction, and non-standard designs such as switchback or cluster-randomized tests.
Hands-on causal inference experience, with sound judgment about when each method applies.
Experience measuring AI, search, recommendation, or retrieval-based systems beyond accuracy alone.
Experience defining event instrumentation from scratch and driving it through an engineering roadmap.
Proficient with SQL and Python; experience applying AI and generative AI tooling to accelerate analysis.
Outstanding communication with technical and non-technical audiences, able to make a crisp recommendation under uncertainty.
Bachelor's or Master's degree in a quantitative field.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
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Bangalore, Karnātaka, India
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