Senior Manager, Data Science

Intuit, Inc.; Bengaluru; Presencial; INR 3 500 000 - 6 000 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Cash bonus

Equity rewards

Resumo da oferta

Intuit, Inc. in Bengaluru, India seeks a Manager 2, Data Science to lead product analytics for the expert routing and AI-powered tools. You will balance leadership of a small team with hands-on data work and partner with product managers to define success before features ship.

You will set metrics, design experiments, apply causal inference, and monitor launches for impact while driving data enablement and instrumentation across the domain.

Qualificações

• 7+ years of analytics and data science experience in product analytics for software/AI products.
• Experience leading and developing analysts and data scientists while staying hands-on.
• Proven partnership with product management and engineering through full product lifecycle: discovery, launch, evaluation, iteration.
• Experience sizing opportunities to prioritize a product roadmap.
• Hands-on experimentation design and analysis, incl. guardrail metrics, variance reduction, non-standard designs.
• Hands-on causal inference experience with judgment on method applicability.
• Experience measuring AI, search, recommendation, or retrieval-based systems beyond accuracy.
• Experience defining event instrumentation from scratch and driving it through an engineering roadmap.
• Proficiency in SQL and Python; applying AI and generative AI tooling to accelerate analysis.
• Outstanding communication with technical and non-technical audiences.

Responsabilidades

• Own the product analytics framework for the expert platform, including event taxonomy and funnel measurement.
• Define outcome metrics for matching and tooling decisions (time to connect, first-contact resolution, satisfaction, etc.).
• Size initiatives and stack rank roadmap with product partners.
• Design and run the experimentation program (switchback, cluster-randomized, interference-aware tests).
• Apply causal inference to isolate product impact amid demand shifts and seasonality.
• Track launches post-deployment and monitor impact over time to catch regressions.
• Evaluate AI-driven experiences against offline and online outcomes.
• Partner with product managers and engineering on roadmap, readiness, and learning.
• Drive data enablement: instrumentation, data quality, and self-serve reporting.
• Set technical standards, review work, and coach on methods and business framing.

Conhecimentos

Analytics leadership

Product analytics

Experiment design

Causal inference

AI tooling

SQL

Python

Communication

Formação académica

Bachelor's or Master's in a quantitative field

Descrição da oferta de emprego

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.