Senior Data Scientist (Fintech)

Location: San Diego, California or Mountain View, California, United States

Salary: $149,500–$202,500 in San Diego; $162,500–$220,000 in Mountain View base pay, plus potential cash bonus, equity rewards, and benefits.

Company

hirify.global is a global financial technology platform serving customers through products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Design, build, and deploy scalable predictive models, including ensemble methods, time-series forecasting, lifetime value, deep learning, and uplift models.
• Own the experimentation pipeline from hypothesis generation and design through causal interpretation and impact quantification.
• Lead causal inference and econometric analyses to identify growth levers and measure incremental impact.
• Define predictive and causally informative success metrics and measurement frameworks.
• Partner with Product Management, Engineering, Data, Customer Success, and Service Delivery teams on Expert Network and AI-driven platform initiatives.
• Present data-driven narratives and quantified strategic recommendations to VP and Director stakeholders.

Requirements

• Master’s degree in Computer Science, Statistics, Econometrics, Data Science, or another quantitative field.
• 4+ years of progressive experience in applied data science roles.
• Expert-level SQL and proficiency in Python or R.
• Experience applying machine learning and causal inference in product-facing applications and integrating models into production, particularly for personalization, recommendation, or AI-assisted user experiences.
• Deep knowledge of experimental design, including non-standard A/B testing, uplift modeling, sequential testing, CUPED, multi-armed bandits, and Bayesian inference.
• Experience with Tableau or Qlik, plus strong communication and analytical storytelling skills.

Nice to have

• Experience with generative AI and other emerging technologies for accelerating insights.

Culture & Benefits

• Cross-functional work across product, engineering, data, customer success, and service delivery.
• Competitive compensation with pay-for-performance rewards.
• Eligibility for cash bonus, equity rewards, and benefits under applicable plans and programs.
• Regular compensation comparisons across ethnicity and gender categories to support fair pay.