Data Manager Jobs at Intuit with Visa Sponsorship
Data Manager jobs at Intuit involve governing the pipelines, taxonomies, and quality frameworks that power products like TurboTax and QuickBooks. The company has a consistent track record of sponsoring international talent across multiple visa categories for data-focused roles, making it a realistic target for skilled candidates who need work authorization.
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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 63+ Data Manager Jobs at Intuit
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Get Access To All JobsTips for Finding Data Manager Jobs at Intuit
Align your credentials to Intuit's data stack
Intuit's Data Manager roles emphasize metadata governance, data quality frameworks, and platforms like dbt or Databricks. Before applying, document hands-on experience with these tools in your resume so your background maps directly to their posted requirements.
Target Intuit's platform and product teams
Data Manager openings at Intuit cluster around product lines like TurboTax, QuickBooks, and Credit Karma. Filtering your search by business unit helps you identify teams with active data governance needs rather than applying to every open role.
Clarify your visa category before the offer stage
Intuit sponsors several visa types for data roles. Knowing whether you need H-1B cap registration, an E-3 application, or OPT extension lets you flag your timeline accurately during recruiter screens, before it becomes a late-stage complication.
Confirm LCA timing with your hiring team
For H-1B and E-3 transfers or new petitions, Intuit's immigration team must file a certified Labor Condition Application with the DOL before your I-129 can be submitted. Ask your recruiter early who coordinates this internally so nothing stalls after your offer.
Use Migrate Mate to surface Intuit's open Data Manager roles
Intuit posts data roles across multiple channels and they fill quickly. Use Migrate Mate to browse current Data Manager openings at Intuit filtered by visa sponsorship type, so you're applying to verified roles that match your specific work authorization situation.
Prepare for PERM documentation if pursuing a Green Card
Intuit has a track record of supporting employees through permanent residency. If that's your goal, organize your degree transcripts, foreign credential evaluations, and prior employment records early. PERM requires precise documentation that can take months to compile under employer deadlines.
Frequently Asked Questions
Does Intuit sponsor H-1B visas for Data Managers?
Yes, Intuit sponsors H-1B visas for Data Manager roles. Data management is a specialty occupation requiring at least a bachelor's degree in a relevant field such as computer science, information systems, or engineering, which satisfies USCIS's core eligibility criteria. Intuit has established immigration processes, so sponsorship for qualified candidates in this function is standard rather than exceptional.
Which visa types does Intuit commonly use for Data Manager roles?
Intuit sponsors H-1B, E-3 visa, TN visa, F-1 OPT, F-1 CPT, J-1 visa, and employment-based Green Card pathways including EB-2 and EB-3 for data-focused positions. Australian citizens targeting Data Manager roles should note the E-3 visa as a practical option with no lottery. Canadian and Mexican professionals with qualifying degrees may also be eligible for TN visa status under the USMCA.
What qualifications and experience does Intuit expect for Data Manager positions?
Intuit's Data Manager roles typically require a bachelor's degree or higher in computer science, data engineering, or a related discipline, combined with practical experience in data governance, metadata management, and pipeline quality. Familiarity with tools like dbt, Databricks, or Collibra is frequently referenced in postings. Roles tied to financial products like TurboTax or QuickBooks may also expect knowledge of regulatory data handling.
How do I apply for Data Manager jobs at Intuit?
You can apply directly through Intuit's careers site, but roles fill quickly and not all postings specify visa sponsorship availability upfront. To save time, browse Data Manager openings at Intuit on Migrate Mate, where listings are filtered by visa sponsorship type so you can confirm your work authorization category matches before investing in the application process.
How do I time my application around H-1B cap registration at Intuit?
USCIS opens H-1B cap registration each March for employment starting October 1. If you're not currently on an employer-sponsored visa or OPT, you'll need Intuit to register your petition during that window. Starting conversations with Intuit recruiters by January gives their immigration team enough runway to prepare your registration and supporting documentation before the annual deadline closes.