Data Scientist Jobs at Intuit with Visa Sponsorship
Data Scientist jobs at Intuit span its financial technology products, including TurboTax, QuickBooks, and Credit Karma, where professionals work on machine learning, personalization, and fraud detection. The company has a consistent track record of sponsoring work visas for this function, supporting candidates through H-1B visa, E-3 visa, and other pathways.
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We are seeking a highly motivated and experienced Sr. Data Scientist to join our Customer Success Data Science team. In this role, you'll drive data-driven strategies to optimize Customer Success outcomes across our Accountants and Partner business, supporting the professionals and firms who serve small and mid-market businesses on Intuit's platform. You will frame the right question before the analysis runs and drive the evidence through to the decision that changes the business, owning the causal identification that isolates what actually moves outcomes. If you're passionate about shaping the future of customer success through data, we'd love to hear from you!
Responsibilities
- Define KPIs and Success Metrics: Frame the right question before any analysis runs and establish the business metrics and causal levers the business manages to, such as onboarding and time-to-value, product adoption, customer health, retention, and growth, ensuring they are measured consistently across reporting surfaces and leadership reviews.
- Strategic Recommendations: Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, including a clear ship-or-iterate call when the model is imperfect.
- Experimentation and Causal Inference: Own the inference approach end to end. Choose and defend the method, whether a randomized experiment, a quasi-experiment, or a predictive model, and isolate what actually moved a metric, including for service and coverage investments where clean randomization is not feasible.
- Predictive Analytics and Modeling: Build and own predictive models such as customer health scoring, churn and expansion propensity, and next best action through their lifecycle, accountable for the outcomes they drive and not only their accuracy.
- Segmentation: Build and apply durable customer segmentation patterns to refine targeting, positioning, service coverage, and customer experience.
- Data Visualizations and Storytelling: Translate complex data into clear, accessible visualizations and author the executive-level communication that helps leaders understand the insight and act on it.
- Enable Self-Serve Analytics: Design, build, and run team data products that are automated, monitored, and reliable enough that the business reviews them each week without rebuilding them by hand. Work with Data Engineering to ensure data quality and enhance real-time analytic capabilities.
- AI Integration: Collaborate with AI teams to integrate AI solutions into business processes, size AI use cases against business value, and automate recurring analytical bottlenecks into agentic systems, owning the agent context so they inherit the team's rigor.
- Cross-Functional Collaboration: Partner with product, digital, customer support, sales, and marketing teams to identify opportunities, create data-driven strategies, and influence decision-making.
Qualifications
- 4+ years of experience working with product analytics, web analytics, customer care analytics, or other customer experience analytics, preferably in fintech
- Advanced proficiency in SQL, "big data" technologies (e.g., Redshift, Spark, Hive, BigQuery), and BI tools (e.g., Tableau, Qlik, Plotly Dash)
- Deep expertise in experimentation design (A/B/n, bandits) and causal inference (Propensity Score, DiD, Synthetic Control) with a strategic understanding of their application, including on small-sample or non-randomized populations where clean control groups are hard to construct
- A track record of framing the question rather than only answering it: taking an ambiguous business problem through to a decision a team acted on
- Experience building and owning predictive models through their lifecycle, with accountability for the business outcomes they drive
- Experience building and maintaining data products that are automated, monitored, and reproducible rather than one-off analyses; directing AI tools to build and review that work is a plus
- Strong business acumen and the ability to translate business strategy into testable hypotheses and learning agendas
- Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership
- Excellent communication and interpersonal skills, with a proven ability to build trust and collaborate seamlessly across technical, business, and cross-functional teams
- Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed
- Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master's Degree preferred
Preferred Qualifications
- Strong programming skills in Python or R; experience building ML and GenAI models, including automation and custom implementations
- Experience evaluating AI-native or non-deterministic systems, including defining what "good" means when outputs vary
- Familiarity with the accounting, bookkeeping, or professional services domain, or an adjacent space such as tax
- Experience solving growth-related problems at financial technology companies serving consumer or SMBs
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 $162,500 - $220,000
Overview
We are seeking a highly motivated and experienced Sr. Data Scientist to join our Customer Success Data Science team. In this role, you'll drive data-driven strategies to optimize Customer Success outcomes across our Accountants and Partner business, supporting the professionals and firms who serve small and mid-market businesses on Intuit's platform. You will frame the right question before the analysis runs and drive the evidence through to the decision that changes the business, owning the causal identification that isolates what actually moves outcomes. If you're passionate about shaping the future of customer success through data, we'd love to hear from you!
Responsibilities
- Define KPIs and Success Metrics: Frame the right question before any analysis runs and establish the business metrics and causal levers the business manages to, such as onboarding and time-to-value, product adoption, customer health, retention, and growth, ensuring they are measured consistently across reporting surfaces and leadership reviews.
- Strategic Recommendations: Provide actionable recommendations using diverse data sets and business knowledge, even when complete data is unavailable, including a clear ship-or-iterate call when the model is imperfect.
- Experimentation and Causal Inference: Own the inference approach end to end. Choose and defend the method, whether a randomized experiment, a quasi-experiment, or a predictive model, and isolate what actually moved a metric, including for service and coverage investments where clean randomization is not feasible.
- Predictive Analytics and Modeling: Build and own predictive models such as customer health scoring, churn and expansion propensity, and next best action through their lifecycle, accountable for the outcomes they drive and not only their accuracy.
- Segmentation: Build and apply durable customer segmentation patterns to refine targeting, positioning, service coverage, and customer experience.
- Data Visualizations and Storytelling: Translate complex data into clear, accessible visualizations and author the executive-level communication that helps leaders understand the insight and act on it.
- Enable Self-Serve Analytics: Design, build, and run team data products that are automated, monitored, and reliable enough that the business reviews them each week without rebuilding them by hand. Work with Data Engineering to ensure data quality and enhance real-time analytic capabilities.
- AI Integration: Collaborate with AI teams to integrate AI solutions into business processes, size AI use cases against business value, and automate recurring analytical bottlenecks into agentic systems, owning the agent context so they inherit the team's rigor.
- Cross-Functional Collaboration: Partner with product, digital, customer support, sales, and marketing teams to identify opportunities, create data-driven strategies, and influence decision-making.
Qualifications
- 4+ years of experience working with product analytics, web analytics, customer care analytics, or other customer experience analytics, preferably in fintech
- Advanced proficiency in SQL, "big data" technologies (e.g., Redshift, Spark, Hive, BigQuery), and BI tools (e.g., Tableau, Qlik, Plotly Dash)
- Deep expertise in experimentation design (A/B/n, bandits) and causal inference (Propensity Score, DiD, Synthetic Control) with a strategic understanding of their application, including on small-sample or non-randomized populations where clean control groups are hard to construct
- A track record of framing the question rather than only answering it: taking an ambiguous business problem through to a decision a team acted on
- Experience building and owning predictive models through their lifecycle, with accountability for the business outcomes they drive
- Experience building and maintaining data products that are automated, monitored, and reproducible rather than one-off analyses; directing AI tools to build and review that work is a plus
- Strong business acumen and the ability to translate business strategy into testable hypotheses and learning agendas
- Strong data storytelling skills, with a proven ability to rapidly construct impactful visualization, communicate insights and influence leadership
- Excellent communication and interpersonal skills, with a proven ability to build trust and collaborate seamlessly across technical, business, and cross-functional teams
- Comfortable working in a fast-paced environment and have flexibility to shift priorities when needed
- Bachelor's degree in Engineering, Data Science, Statistics, Mathematics, Computer Science, Economics or related quantitative field; Master's Degree preferred
Preferred Qualifications
- Strong programming skills in Python or R; experience building ML and GenAI models, including automation and custom implementations
- Experience evaluating AI-native or non-deterministic systems, including defining what "good" means when outputs vary
- Familiarity with the accounting, bookkeeping, or professional services domain, or an adjacent space such as tax
- Experience solving growth-related problems at financial technology companies serving consumer or SMBs
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 $162,500 - $220,000
See all 41+ Data Scientist Jobs at Intuit
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Get Access To All JobsTips for Finding Data Scientist Jobs at Intuit
Tailor your portfolio to Intuit's products
Intuit's Data Scientist roles center on financial data, customer behavior modeling, and tax product personalization. Projects demonstrating ML applied to transactional data, recommendation systems, or fraud detection align directly with what hiring managers are evaluating.
Clarify sponsorship eligibility before applying
Intuit sponsors multiple visa types, including H-1B, E-3, and TN. Know which category applies to your citizenship before your recruiter screen. Australians targeting E-3 or Canadians using TN should confirm the role qualifies as a specialty occupation at the offer stage.
Account for LCA filing in your start date
Before USCIS can adjudicate an H-1B or E-3 petition, your employer must file a certified Labor Condition Application with the DOL. Build at least two to three weeks into your expected start date to allow for LCA certification before the I-129 is filed.
Highlight cross-functional collaboration experience
Intuit's Data Scientist interviews test both technical depth and ability to translate analysis into product decisions. Demonstrating experience working alongside engineers, product managers, or growth teams directly reflects how these roles operate inside their business units.
Use Migrate Mate to filter open roles by sponsorship
Intuit posts Data Scientist openings across multiple business units with varying sponsorship terms. Use Migrate Mate to surface roles that explicitly support your visa category and avoid wasting applications on positions where sponsorship is unavailable.
Protect your OPT or grace period timeline
If you're on F-1 OPT, Intuit can support CPT and post-completion OPT. STEM OPT extensions give you up to 24 additional months, but your employer must be E-Verify enrolled. Confirm Intuit's participation before your standard OPT expiration to avoid a gap in work authorization.
Frequently Asked Questions
Does Intuit sponsor H-1B visas for Data Scientists?
Yes, Intuit sponsors H-1B visas for Data Scientist roles. The H-1B is a specialty occupation visa that requires a bachelor's degree or higher in a directly related field, which Data Scientist positions typically satisfy. Because the H-1B is subject to an annual cap and lottery, timing your application cycle and confirming the role qualifies before accepting an offer is important.
How do I apply for Data Scientist jobs at Intuit?
Applications go through Intuit's careers portal, where roles are listed by business unit, including TurboTax, QuickBooks, Mint, and Credit Karma. Before applying, confirm the posting explicitly mentions visa sponsorship or verify with the recruiter early in the process. Migrate Mate lets you browse Intuit's open Data Scientist roles filtered by visa sponsorship availability, which saves time when multiple openings are live simultaneously.
Which visa types does Intuit commonly use for Data Scientist roles?
Intuit sponsors H-1B, E-3, TN visa, and EB-2 or EB-3 Green Card pathways for Data Scientists, along with F-1 OPT and CPT for students. Australian citizens frequently use the E-3, which has no lottery and faster timelines. Canadian and Mexican nationals with qualifying credentials can pursue the TN visa classification. The right pathway depends on your citizenship, degree, and where you are in your career.
What qualifications does Intuit expect for Data Scientist roles?
Most Data Scientist postings at Intuit require a bachelor's or master's degree in statistics, computer science, mathematics, or a closely related field, along with hands-on experience in Python, SQL, and machine learning frameworks. Senior roles typically expect experience with large-scale data pipelines, A/B testing, and causal inference. A portfolio with applied work on financial data, customer segmentation, or predictive modeling strengthens your candidacy significantly.
How do I time the visa filing process when starting at Intuit?
For H-1B transfers or cap-exempt filings, USCIS standard processing can take two to four months. Premium processing reduces this to 15 business days. For E-3, consular processing in Australia typically takes two to six weeks after the LCA is certified by the DOL. Align your offer acceptance and intended start date with these timelines so your authorization is in place before your first day.