This listing doesn't post a salary. Most similar roles pay
$145,200–$228,250.
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
210 open roles
on FindRole.
Listed pay typically runs
$202,500–$274,000
across 187 roles with salary data.
The Senior Staff Data Scientist, Finance Data Science joins a team that transforms complex financial and customer data into scalable operating processes and growth opportunities. In this role, you will lead ambiguous analytical problems by framing questions, defining metrics, and establishing causal levers for strategy, planning, and reporting. You will build shared data products, semantic models, pipelines, and AI-enabled workflows while establishing quality standards and governance. Key responsibilities include applying causal inference, experiments, and synthetic tests to resolve attribution questions and turning bottlenecks into agentic workflows. You must possess advanced SQL and programming skills in Python or R, alongside deep expertise in statistical reasoning and predictive modeling. This role solves critical business problems involving LTV, retention, pricing, and forecasting within a subscription and revenue data context.
What does a Data Scientist earn?
Median $171650 from 280 postings across 62 companies.
Frame and lead cross-team analytical problems involving growth, retention, pricing, and forecasting.
Define the metrics, business logic, and causal levers used by leaders to manage performance.
Build and own shared data products, semantic models, pipelines, and decision systems.
Translate complex data into actionable recommendations, investment choices, and executive narratives.
Apply causal inference, experiments, and synthetic tests to resolve contested attribution questions.
Develop scalable AI and agentic workflows by defining quality standards and evaluation frameworks.
Establish quality standards, monitoring, and governance for data products supporting financial decisions.
Raise the analytical bar through technical leadership, coaching, and establishing reusable methods.
What we're looking for
10+ years of relevant experience in data science, analytics, finance, strategy, or a related field.
Bachelor’s degree in a quantitative field like Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, Finance, or equivalent practical experience.
Strong business judgment and financial acumen to connect customer, subscription, and revenue data to business outcomes.
Advanced SQL and programming skills in Python, R, or a comparable language with experience in large-scale data platforms.
Deep understanding of statistical reasoning, causal inference, experimentation, and predictive modeling.
Experience leading ambiguous, cross-functional problems and designing data products, analytical models, and pipelines through their lifecycle.
Experience evaluating AI-enabled or non-deterministic systems using golden datasets, structured testing, or synthetic data.
Strong written and verbal communication skills to author executive-level narratives and influence leaders across organizations.
Experience with SaaS, subscription, or customer lifecycle businesses (preferred).
Experience with LTV, retention, ARPC, pricing, forecasting, or external reporting (preferred).
Experience building AI-enabled analytical workflows, agent context, or delegation governance (preferred).
Experience partnering with Engineering or Data Platform teams to turn prototypes into production data products (preferred).
Python
SQL
Machine Learning
Predictive Modeling
Statistics
Scikit-learn
Pandas
NumPy
Tableau
Qlik
Plotly Dash
Git
Linux
Generative AI
A/B Testing
Version Control
Data Analysis