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Senior Manager, Data Science

Category Data Location Bangalore, India Job ID 24207
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Company Overview

Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With tens of millions of customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Job Overview

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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Ercan Kaynakca Staff Data Crypto Analyst

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