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Staff Data Scientist

Mountain View, California, United States; New York, United States

Actively hiring, first seen by us 12 days ago
Pay
$194,000–262,500/year · BaseAnnual period assumed — pay source
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. The expected base pay range for this position is: Mountain View $194,000 - $262,500
Read the full posting
Work setting
Not stated
Employment
Not stated

Before you apply

Employer’s visa record
1,932 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.

What you’ll work on

Full posting
  • Lead end-to-end analyses using causal inference and A/B tests to measure impact

  • Size and prioritize growth opportunities across the messaging customer journey

  • Build scalable measurement frameworks and success metrics for messaging products

  • Build predictive models and customer segmentation to optimize adoption and retention

  • Build reusable analytical tools and self-service data products

From the employer’s posting
Lead complex, end-to-end analytical investigations using advanced statistics, SQL, Python, machine learning, and causal inference
Identify, size, and prioritize high-impact growth opportunities across the messaging customer journey
Develop scalable measurement frameworks and define success metrics to evaluate messaging product performance
Apply machine learning, predictive modeling, and customer segmentation to uncover behavioral patterns
Build reusable analytical frameworks, automated insights, opportunity-sizing tools, and self-service data products

What you’ll bring

All qualifications

Core experience

  • 8+ years of experience in Data Science, Product Analytics, or a related quantitative discipline, with a demonstrated track record of driving measurable customer, product, and revenue impact in SaaS, marketing technology, or digital products.
  • Deep expertise in advanced analytics, experimentation, and causal inference, including A/B testing and quasi-experimental methods (e.g., difference-in-differences, matching, synthetic control, regression discontinuity).
  • Demonstrated ability to select and apply rigorous methodologies to ambiguous business problems and quantify incremental impact.
  • Experience building scalable data products and analytical frameworks, including automated insights, opportunity-sizing tools, and self-service solutions that improve decision-making and extend Data Science impact beyond individual analyses.
  • Proven ability to navigate ambiguity and influence cross-functional stakeholders, independently leading complex analytical initiatives and translating insights into strategic recommendations that drive measurable business outcomes.

Preferred experience

  • Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative field; advanced degree preferred.
  • Experience in messaging, marketing automation, communications platforms, or omnichannel customer engagement, including SMS, WhatsApp, RCS, or email marketing.
  • Experience with SaaS monetization, usage-based pricing, product-led growth, and customer lifecycle optimization.
Qualification wording
8+ years of experience in Data Science, Product Analytics, or a related quantitative discipline, with a demonstrated track record of driving measurable customer, product, and revenue impact in SaaS, marketing technology, or digital products.
Deep expertise in advanced analytics, experimentation, and causal inference, including A/B testing and quasi-experimental methods (e.g., difference-in-differences, matching, synthetic control, regression discontinuity). Demonstrated ability to select and apply rigorous methodologies to ambiguous business problems and quantify incremental impact.
Experience building scalable data products and analytical frameworks, including automated insights, opportunity-sizing tools, and self-service solutions that improve decision-making and extend Data Science impact beyond individual analyses.
Proven ability to navigate ambiguity and influence cross-functional stakeholders, independently leading complex analytical initiatives and translating insights into strategic recommendations that drive measurable business outcomes.
Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative field; advanced degree preferred.
Experience in messaging, marketing automation, communications platforms, or omnichannel customer engagement, including SMS, WhatsApp, RCS, or email marketing.
Experience with SaaS monetization, usage-based pricing, product-led growth, and customer lifecycle optimization.
Education & alternatives
- Exceptional communication and data storytelling skills, with demonstrated ability to influence senior leadership, communicate complex technical concepts clearly, and drive alignment across Product, Engineering, Design, Finance, and Marketing. - Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative field; advanced degree preferred. Preferred Qualifications
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Posting record

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Actively hiringFirst seen by us 12 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 202612 days ago
Recorded sightings
13
Last seen by us
Nov 14, 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

Higher than most similar jobs

$194K–$263K against $118K–$195K, the middle half of what similar US postings state.

From 3,828 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 12

Similar jobs usually come down between day 8 and day 60.

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

From 11,862 similar postings that came down, and 76 of Intuit’s. Coming down is not always a hire.

Intuit is hiring

57 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 and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • NumPy
  • pandas
  • scikit-learn
Where the posting names them
- Product Strategy & Revenue Growth: Identify, size, and prioritize high-impact growth opportunities across the messaging customer journey, including acquisition, adoption, activation, engagement, monetization, and retention. Translate ambiguous business challenges into rigorous analytical frameworks and actionable recommendations that accelerate customer and revenue growth. - Advanced Analytics & Causal Inference: Lead complex, end-to-end analytical investigations using advanced statistics, SQL, Python, machine learning, and causal inference. Design and evaluate A/B tests and quasi-experiments (e.g., difference-in-differences, matching, synthetic control) to establish causal relationships, quantify incremental impact, and guide product decisions. - Measurement Strategy & Experimentation: Develop scalable measurement frameworks and define success metrics to evaluate messaging product performance, customer outcomes, and business impact. Champion experimentation best practices and analytical rigor to enable faster, more confident decision-making.
- Strong foundation in predictive modeling and machine learning, including customer segmentation, propensity modeling, churn prediction, with experience translating models and insights into actionable product and business decisions. - Advanced proficiency in SQL and Python (e.g., pandas, NumPy, scikit-learn, statsmodels), with hands-on experience analyzing large, complex datasets, developing statistical models, and building scalable analytical solutions. - Strong product and business acumen, with experience identifying and sizing growth opportunities, evaluating product performance, and influencing strategies related to customer acquisition, adoption, engagement, monetization, and retention.

Your next step

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

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About Intuit

People
About 18,600 in 2026, up 2% from the year before.Annual report (SEC Form 10-K)
Company
Listed as INTU.
H-1B visas
450 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Layoff notices
Notices this year and last cover 1,027 people. The latest was filed May 20, 2026.State WARN notices

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,403, the most 2,949, and the latest week had 2,098.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

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 ↗

Mailchimp is a leading marketing automation platform that empowers millions of businesses to grow through powerful, easy-to-use marketing and messaging solutions. As we expand beyond email into omnichannel customer engagement, Messaging is at the forefront of Mailchimp's growth strategy, helping businesses connect with their customers through SMS, WhatsApp, RCS, and other emerging communication channels.


Come join the Mailchimp Product Data Science team as a Staff Data Scientist supporting Messaging, one of our most exciting and strategically important growth areas. We are looking for a creative, business-minded problem solver who is passionate about leveraging data science to unlock customer value, accelerate product innovation, and drive measurable business impact.


As a Staff Data Scientist, you will serve as a senior individual contributor and strategic thought partner to Product, Engineering, Design, Finance, and Product Marketing leaders. You will tackle complex, high-impact business problems across the messaging customer journey—from adoption and engagement to monetization, retention, and revenue growth. Your expertise in advanced analytics, experimentation, causal inference, machine learning, and automation will be instrumental in identifying growth opportunities, shaping product strategy, and influencing investment decisions.


This role offers a unique opportunity to help shape the future of Mailchimp's omnichannel messaging strategy. You will lead strategic research, develop scalable data products and measurement frameworks, and translate complex insights into actionable recommendations that influence product roadmaps and accelerate business outcomes. Beyond individual projects, you will help elevate data science capabilities across teams, break down organizational silos, and establish analytical approaches that scale across the broader Mailchimp ecosystem.


Responsibilities

  • Strategic Data Partnership & Influence: Serve as a trusted data science partner to Product, Engineering, Design, Finance, and Product Marketing leaders, shaping Mailchimp's omnichannel messaging strategy across SMS, WhatsApp, RCS, and emerging channels. Influence product roadmaps, investment priorities, and business decisions through data-driven insights.
  • Product Strategy & Revenue Growth: Identify, size, and prioritize high-impact growth opportunities across the messaging customer journey, including acquisition, adoption, activation, engagement, monetization, and retention. Translate ambiguous business challenges into rigorous analytical frameworks and actionable recommendations that accelerate customer and revenue growth.
  • Advanced Analytics & Causal Inference: Lead complex, end-to-end analytical investigations using advanced statistics, SQL, Python, machine learning, and causal inference. Design and evaluate A/B tests and quasi-experiments (e.g., difference-in-differences, matching, synthetic control) to establish causal relationships, quantify incremental impact, and guide product decisions.
  • Measurement Strategy & Experimentation: Develop scalable measurement frameworks and define success metrics to evaluate messaging product performance, customer outcomes, and business impact. Champion experimentation best practices and analytical rigor to enable faster, more confident decision-making.
  • Scalable Data Products & AI Innovation: Build reusable analytical frameworks, automated insights, opportunity-sizing tools, and self-service data products that democratize access to insights and scale Data Science impact. Leverage modern AI/ML techniques and AI-assisted tools to accelerate analytical workflows and improve organizational productivity.
  • Predictive Modeling & Customer Intelligence: Apply machine learning, predictive modeling, and customer segmentation to uncover behavioral patterns, identify growth opportunities, and optimize messaging adoption, engagement, and customer lifetime value.
  • Data Quality & Cross-Functional Collaboration: Partner with Data Engineering and platform teams to improve data instrumentation, quality, reliability, and accessibility. Break down organizational silos by developing consistent metrics, sharing learnings, and scaling analytical solutions across messaging channels and the broader Mailchimp ecosystem.
  • Executive Communication & Technical Leadership: Translate complex analytical findings into compelling, actionable narratives for technical and nontechnical stakeholders, including senior leadership. Provide technical thought leadership, mentor peers, and elevate the organization's standards for data-driven decision-making, experimentation, and innovation.

Qualifications

  • 8+ years of experience in Data Science, Product Analytics, or a related quantitative discipline, with a demonstrated track record of driving measurable customer, product, and revenue impact in SaaS, marketing technology, or digital products.
  • Deep expertise in advanced analytics, experimentation, and causal inference, including A/B testing and quasi-experimental methods (e.g., difference-in-differences, matching, synthetic control, regression discontinuity). Demonstrated ability to select and apply rigorous methodologies to ambiguous business problems and quantify incremental impact.
  • Strong foundation in predictive modeling and machine learning, including customer segmentation, propensity modeling, churn prediction, with experience translating models and insights into actionable product and business decisions.
  • Advanced proficiency in SQL and Python (e.g., pandas, NumPy, scikit-learn, statsmodels), with hands-on experience analyzing large, complex datasets, developing statistical models, and building scalable analytical solutions.
  • Strong product and business acumen, with experience identifying and sizing growth opportunities, evaluating product performance, and influencing strategies related to customer acquisition, adoption, engagement, monetization, and retention.
  • Experience building scalable data products and analytical frameworks, including automated insights, opportunity-sizing tools, and self-service solutions that improve decision-making and extend Data Science impact beyond individual analyses.
  • Working fluency with modern AI tools and workflows, including LLM-based coding assistants (e.g., Cursor, Claude) and AI-assisted analytics, with the ability to accelerate analytical development while maintaining high standards for accuracy, reproducibility, and rigor.
  • Proven ability to navigate ambiguity and influence cross-functional stakeholders, independently leading complex analytical initiatives and translating insights into strategic recommendations that drive measurable business outcomes.
  • Exceptional communication and data storytelling skills, with demonstrated ability to influence senior leadership, communicate complex technical concepts clearly, and drive alignment across Product, Engineering, Design, Finance, and Marketing.
  • Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative field; advanced degree preferred.


Preferred Qualifications

  • Experience in messaging, marketing automation, communications platforms, or omnichannel customer engagement, including SMS, WhatsApp, RCS, or email marketing.
  • Experience with SaaS monetization, usage-based pricing, product-led growth, and customer lifecycle optimization.
  • Demonstrated technical leadership through mentoring, establishing analytical best practices, and scaling data science capabilities across teams.

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. 

The expected base pay range for this position is:
Mountain View $194,000 - $262,500
Source details

View original posting ↗

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Pay
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. The expected base pay range for this position is: Mountain View $194,000 - $262,500
Location & working pattern

Mountain View, California, United States; New York, United States

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

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