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Fintech Data Science Jobs in California (NOW HIRING)

Taskrabbit

Staff Data Scientist

San Francisco, CA

$170K - $225K/yr

A minimum of 7 years industry experience in data science; previous experience in a marketplace or fintech company is a plus * Strong and relevant experience with advanced experimentation and ...

Found

Senior Data Scientist (Risk)

San Francisco, CA · On-site

$163 - $225/hr

You will work closely with our Engineering, Data Science, Product, and Operations teams to build ... You may also have: * Previous experience working at a fintech. * Previous startup experience.

Mudflap

Senior Data Scientist, Risk

Palo Alto, CA · On-site

$185K - $225K/yr

... fintech platform that processes billions in annual payment volume. We're building a data-driven ... Drive strategic data science initiatives that directly impact business outcomes, working closely ...

Jobzhr

Data Scientist (AHL)

San Mateo, CA · On-site

$140 - $160/hr

Since 2002, Achieve has grown into one of the largest private consumer fintech unicorns in the U.S ... Serve as a strategic thought partner for other members of the Data Science team Qualifications What ...

Achieve

Data Scientist (AHL)

San Mateo, CA · On-site

$140K - $160K/yr

Since 2002, Achieve has grown into one of the largest private consumer fintech unicorns in the U.S ... Serve as a strategic thought partner for other members of the Data Science team Qualifications What ...

Achieve

Data Scientist (AHL)

San Mateo, CA

Since 2002, Achieve has grown into one of the largest private consumer fintech unicorns in the U.S ... Serve as a strategic thought partner for other members of the Data Science team Qualifications What ...

1 point system

Data Analyst

Sunnyvale, CA · On-site

Master's degree in data science, Statistics, Computer Science, Economics, or a related field. * 4+ years of industry experience in Payments, Risk, FinTech, or Marketplace Analytics. * Proven ability ...

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All JobsFintech Data Science JobsFintech Data Science Jobs in California

Fintech Data Science information

See California salary details

$37K

$121.1K

$193.9K

How much do fintech data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for fintech data science in California is $121,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a fintech data scientist?

A Fintech Data Scientist is a professional who uses data analysis, machine learning, and statistical techniques to solve problems and create value within the financial technology (fintech) industry. They work with large amounts of financial data to develop predictive models, detect fraud, assess risk, and optimize financial products or services. Their expertise combines knowledge of finance, programming, and advanced analytics to help fintech companies make data-driven decisions and innovate in areas such as payments, lending, and investment. Fintech Data Scientists often collaborate with engineers, product managers, and business stakeholders to deliver actionable insights that drive business growth.

What are the key skills and qualifications needed to thrive as a fintech data scientist?

To thrive as a Fintech Data Scientist, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, mathematics, or a related field). Familiarity with tools such as Python, R, SQL, cloud computing platforms, and experience with financial data modeling or relevant certifications are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills that set top professionals apart. These skills and qualities are vital for extracting actionable insights from complex financial data, driving innovation, and ensuring regulatory compliance in the fast-evolving fintech industry.

How do fintech data scientists typically collaborate with product and engineering teams to develop new financial products?

In fintech, data scientists often work closely with product managers and engineering teams throughout the lifecycle of a financial product. They analyze user data and market trends to provide actionable insights during the product design phase, and collaborate with engineers to implement machine learning models into the product infrastructure. Regular cross-functional meetings and agile workflows are common, allowing data scientists to iterate on models based on feedback and evolving requirements. This collaborative environment ensures that data-driven solutions are robust, scalable, and aligned with business goals.

What is the difference between Fintech Data Science vs Fintech Data Analyst?

AspectFintech Data ScienceFintech Data Analyst
Required SkillsAdvanced statistical, programming, and machine learning skillsData interpretation, reporting, and basic analytics
CertificationsData Science certifications, programming coursesData analysis or business intelligence certifications
Work EnvironmentDeveloping models, algorithms, and predictive analyticsData reporting, dashboards, and data cleaning
Industry UsageCreating predictive models for risk, fraud detection, and customer insightsGenerating reports, supporting decision-making with data

Fintech Data Science involves building complex models and applying machine learning techniques, requiring advanced skills and certifications. Fintech Data Analysts focus on interpreting data, creating reports, and supporting business decisions with less technical complexity. Both roles are essential in the fintech industry but differ in technical depth and responsibilities.

Is data science good for fintech?

Data science is highly valuable in fintech, as it enables the development of algorithms for risk assessment, fraud detection, and personalized financial services. Fintech companies often rely on data analysis, machine learning, and statistical modeling to improve decision-making and customer experience. Skills in programming, data manipulation, and financial knowledge are essential for data scientists in this field.

Is fintech data science a high paying career?

Fintech data science is generally a high-paying career due to the demand for advanced analytics and machine learning skills in financial technology companies. Salaries often depend on experience, education, and technical expertise in tools like Python, R, and SQL, with senior roles earning significantly more. The field offers competitive compensation compared to many other data science roles across industries.

What are popular job titles related to Fintech Data Science jobs in California?

For Fintech Data Science jobs in California, the most frequently searched job titles are:

What job categories do people searching Fintech Data Science jobs in California look for?

The top searched job categories for Fintech Data Science jobs in California are:

What cities in California are hiring for Fintech Data Science jobs?

Cities in California with the most Fintech Data Science job openings:

Fintech Data Science jobs near you
Infographic showing various Fintech Data Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Staff Data Scientist

Taskrabbit

San Francisco, CA

$170K - $225K/yr

Full-time

Posted 24 days ago

Job description

Prior to applying please note:

  • We are currently unable to provide visa sponsorship for this position (including H-1B, OPT, F1, CPT or other employment-based visas). Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future. 
  • This role is hybrid requiring 2 days in office at our San Francisco hub every Tuesday & Wednesday (located at 130 Sutter St, San Francisco, CA). 
About the Role

Data Science plays a crucial role in driving impact at Taskrabbit. As a member of the team, you will help drive our business strategy forward through predictive insights. We are seeking a highly skilled and motivated Staff Data Scientist to join us, working closely with cross-functional teams from product, finance, engineering, risk and operations to provide data-driven insights and solutions that enhance our products and accelerate growth while minimizing marketplace losses. 

What you will work on
  • Be a strategic thought partner with stakeholders from product, risk, finance, engineering, and operations to define high-impact analytical problems, and solve them using different analytical and statistical approaches. Present actionable insights in a clear and compelling manner.
  • Proactively perform analytical deep dives to identify strategic growth opportunities in key business levers with a focus on commerce and risk
  • Collaborate with stakeholders to define and measure success metrics for new features and products, conduct advanced experimentation and causal inference to optimize product features and user experiences
  • Design, develop, and scale proactive fraud interventions using heuristic and/or machine learning models. These efforts will be focused on enhancing financial performance by mitigating issues such as chargebacks, fraud, transaction declines, and refunds.
  • Foster a data-driven culture within the organization by advocating for best practices in data analysis and interpretation.
Who you are
  • BS, MS or Ph.D. in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research, or related field).
  • A minimum of 7 years industry experience in data science; previous experience in a marketplace or fintech company is a plus
  • Strong and relevant experience with advanced experimentation and statistical modeling; you have past experience with fraud/risk models in a marketplace/fintech context
  • Excellent analytical and problem-solving skills.
  • Excellent business acumen and strategic thinking skills, especially in a commerce/risk domain
  • Expert in SQL, experienced in Python, and familiar with data pipeline tooling (e.g. dbt) and git. Bonus points for experience in productionizing ML models and familiarity with ML Ops.
  • A self-starter with the ability to work independently and drive your own projects end-to-end with a track record of landing strong business impact 
  • Ability to communicate complex data findings in a clear and concise manner to an executive audience.
Compensation & Benefits: 

At Taskrabbit, our approach to compensation is designed to be competitive, transparent, and equitable. Total compensation consists of base pay + bonus + benefits + perks.

The base pay range for this position is $170,000 - $225,000. This range is representative of base pay only, and does not include any other total cash compensation amounts, such as company bonus or benefits. Final offer amounts may vary from the amounts listed above and will be determined by factors including, but not limited to, relevant experience, qualifications, geography, and level.

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