Back to jobs

Staff Data Scientist - Engagement

Charlotte, North Carolina, United States; Oakland, California, United States

Actively hiring, first seen by us 2 days ago
Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Own the analytics agenda for the Subscriptions product area

  • Apply ML and causal inference to churn, renewal, and pricing experiments

  • Design and run A/B and quasi-experimental tests of member experience changes

  • Build member segmentation to guide targeting, personalization, and offers

  • Partner with Product, Engineering, and Design leaders on roadmap decisions

From the employer’s posting
Own the analytics agenda for the Subscriptions product area
Apply ML and causal inference techniques to subscriptions-specific problems such as churn prediction, renewal optimization, and pricing or packaging experiments
Design and execute experiments (A/B/n, and quasi-experimental designs where testing is constrained)
Analyze member behavior within Subscriptions to build segmentation that improves targeting, personalization, and offer strategy
Partner with product leadership: Combine data insights with business acumen to partner with Product, Engineering, and Design leaders in shaping roadmap and prioritization decisions

What you’ll bring

All qualifications

Core experience

  • Ability to translate ambiguous product questions into structured analyses and actionable recommendations.
  • Experience designing and interpreting experiments, with working knowledge of causal inference techniques for use when experimentation is constrained.
  • Solid understanding of customer segmentation and experimentation design, with the judgment to balance statistical rigor and business considerations.
  • Experience contributing to reusable analytical frameworks, methodologies, or tools used by others on the team.
  • Strong communication and stakeholder-influence skills, with the ability to work effectively with Director-level partners across business and technical teams.
  • Ability to navigate ambiguity, make fast data-driven decisions, and operate effectively in a fast-paced, dynamic environment.

Preferred experience

  • 7+ years of experience in data science and analytics, with a track record of driving impact within a product area or initiative; experience with subscription, membership, or lifecycle-based products strongly preferred, fintech experience a plus.
Qualification wording
Ability to translate ambiguous product questions into structured analyses and actionable recommendations.
Experience designing and interpreting experiments, with working knowledge of causal inference techniques for use when experimentation is constrained.
Solid understanding of customer segmentation and experimentation design, with the judgment to balance statistical rigor and business considerations.
Experience contributing to reusable analytical frameworks, methodologies, or tools used by others on the team.
Strong communication and stakeholder-influence skills, with the ability to work effectively with Director-level partners across business and technical teams.
Ability to navigate ambiguity, make fast data-driven decisions, and operate effectively in a fast-paced, dynamic environment.
7+ years of experience in data science and analytics, with a track record of driving impact within a product area or initiative; experience with subscription, membership, or lifecycle-based products strongly preferred, fintech experience a plus.
Apply at Intuit

Posting record

Report an error

Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20262 days ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 7 and day 55.

At Intuit, jobs usually come down by about day 22.

From 10,129 similar postings that came down, and 64 of Intuit’s. Coming down is not always a hire.

Intuit is hiring

59 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring is picking up
  • Takes jobs down quickly
Hiring record

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Your next step

Complete your application on jobs.intuit.com. The employer’s form will show what is required.

Applying through Radancy (TalentBrew)

  • Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.

Already applied? Track this application

Has Intuit posted this job before?

Yes. We’ve followed one other Staff Data Scientist - Engagement job there since November 2026. It is still up.

  1. OaklandStill up after 2 days, first seen Nov 2
  2. This jobUp 2 days so far, first seen Nov 2

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Intuit's Consumer Group is committed to building tools and services that improve our members' financial journeys. At the heart of this mission, the Credit Karma Engagement team builds in-product features and experiences that help members take meaningful action to improve their financial outcomes, from building credit, to saving money, to paying down debt.

The team is seeking a Staff Data Scientist to serve as an analytical partner to our Subscriptions product team, responsible for using data to improve the member experience across the subscription lifecycle, from trial and conversion through renewal and retention. This is a high-impact role where you will bring scientific rigor to product decisions, partner closely with Product and Engineering, and help shape how we measure and grow subscription value for our members.


Responsibilities

  • Drive analytics strategy for Subscriptions: Own the analytics agenda for the Subscriptions product area, mapping the member journey end to end, from trial and onboarding through conversion, renewal, and cancellation, to identify the highest-leverage opportunities.
  • Partner with product leadership: Combine data insights with business acumen to partner with Product, Engineering, and Design leaders in shaping roadmap and prioritization decisions.
  • Apply advanced analytical methods: Apply ML and causal inference techniques to subscriptions-specific problems such as churn prediction, renewal optimization, and pricing or packaging experiments, adapting existing frameworks or building new ones as needed.
  • Design and run experiments: Design and execute experiments (A/B/n, and quasi-experimental designs where testing is constrained) to evaluate changes to the member experience and quantify their impact on member and business outcomes.
  • Build member segmentation: Analyze member behavior within Subscriptions to build segmentation that improves targeting, personalization, and offer strategy.
  • Contribute to the AI-native roadmap: Partner with the team to identify opportunities to apply AI/ML within the subscriptions experience, help design measurement plans, and connect model performance to member and business outcomes.
  • Mentor and support the team: Mentor other data scientists on best practices and experimentation rigor, and contribute to hiring and calibration as needed.

Qualifications

We're looking for a curious, proactive data scientist with a passion for driving member engagement and retention.


  • 7+ years of experience in data science and analytics, with a track record of driving impact within a product area or initiative; experience with subscription, membership, or lifecycle-based products strongly preferred, fintech experience a plus.
  • Ability to translate ambiguous product questions into structured analyses and actionable recommendations.
  • Experience designing and interpreting experiments, with working knowledge of causal inference techniques for use when experimentation is constrained.
  • Solid understanding of customer segmentation and experimentation design, with the judgment to balance statistical rigor and business considerations.
  • Exposure to lightweight Machine Learning in terms of being able to build offline classification & regression models to inform business decisions.
  • Experience contributing to reusable analytical frameworks, methodologies, or tools used by others on the team.
  • Strong communication and stakeholder-influence skills, with the ability to work effectively with Director-level partners across business and technical teams.
  • Ability to navigate ambiguity, make fast data-driven decisions, and operate effectively in a fast-paced, dynamic environment.
  • Ability to use AI-native tools to plan, implement, and synthesize analyses across use cases ranging from experiment readouts to retention/churn deep dives.
  • BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related 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. 

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Charlotte, North Carolina, United States; Oakland, California, United States

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.