below marketmost similar roles pay hereabove market
This role pays more than
91%
of similar roles. Most pay
$165,375–$220,925
— the blue band above.
At the midpoint, this role pays about
$275k
versus about
$193k
for comparable roles.
Based on 240 similar postings.
Employer
About Intuit
Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology
Intuit currently has
224 open roles
on FindRole.
Listed pay typically runs
$202,500–$274,000
across 203 roles with salary data.
Manager 3, Data Science - Data Foundations joins the Customer Success Data Science & Analytics team to lead the Data Foundations group. This hands-on-adjacent people-leadership role involves managing senior and staff-level data scientists to build a governed, compliant data foundation for analytics and AI capabilities. You will set technical direction, own the roadmap, and manage the financial case for data products. Key responsibilities include establishing metric standardization, building semantic knowledge layers, and developing agentic tooling for automated root-cause analysis and pipeline migration. You will utilize SQL, Python, and modern cloud data platforms to solve complex data-governance problems. The work focuses on creating trusted entities, managing PII minimization, and stitching behavioral clickstream and time-series journeys to optimize customer success outcomes and reduce downstream data failures.
What does a Data Science Manager earn?
Median $211200 from 40 postings across 11 companies.
Lead, coach, and grow a team of senior and staff-level data scientists to deliver governed data foundations.
Own the strategic vision, roadmap, and financial case for the Data Foundations portfolio.
Establish governed clean entities, standardized metric layers, and semantic knowledge layers as the source of truth.
Develop KPI frameworks and metric standardization models across core data domains.
Drive a shift-left approach to data quality by embedding data design into the product development lifecycle.
Lead custom implementations of AI/GenAI capabilities and agentic data tooling for automation and productivity.
Manage compliance and security execution for the data estate, including PII minimization and access control.
Negotiate ownership boundaries with Data Engineering and Product partners on governed base tables and platforms.
What we're looking for
BS or MS in Statistics, Mathematics, Computer Science, Economics/Econometrics, Operations Research, Engineering, or a related quantitative field.
14+ years of experience in data science, analytics, or data platform work.
5+ years of experience directly managing data scientists or analytics engineers.
Demonstrated success leading teams delivering governed data foundations, metric standardization, domain modeling, or data product ownership at enterprise scale.
Strong hands-on technical foundation in SQL and Python to set architectural direction and review team code.
Experience with modern cloud data platforms, pipeline orchestration, and migrating legacy analytics estates.
Proven track record building AI/GenAI or agentic capabilities to automate data operations like validation and root-cause analysis.
Experience owning a multi-million-dollar impact portfolio, including building the financial case and reporting to executive forums.
Experience with data governance and compliance regimes (e.g., IRS 7216, GDPR, CCPA) (preferred).
Background in semantic layers, knowledge graphs, or knowledge-layer design for AI/agent consumption (preferred).
Data Science
Python
R
SQL
Predictive Modeling
Prescriptive Modeling
Causal Inference
Experimentation
AI
Cloud Data Environments
Data Workflow Management
Psychometric Research
Workforce Forecasting