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Data Scientist Risk Jobs in California (NOW HIRING)

Retool Inc.

Data Scientist

San Francisco, CA · On-site

$182K - $250K/yr

That's both an opportunity and a challenge: as more people build with more AI tools, the risk of ... We're looking for a Data Scientist to join our Data Science & Analytics team to help Retool make ...

Edwards Lifesciences

Data Scientist

Irvine, CA · On-site

As a Senior Data Scientist, you own modeling for a clinical or product domain, drive problem ... risk documentation. What you'll need (Required): Bachelor's in related field (e.g., Computer ...

New

East West Bank

Financial Crimes Data Scientist

Pasadena, CA · On-site

$100K - $200K/yr

Develop risk-scoring, anomaly detection, predictive, and network analytics models using internal ... Hands-on experience with data science tools * Problem-solving aptitude * Analytical mind and great ...

Oscar Health

Data Scientist II

Los Angeles, CA · On-site

$131K - $172K/yr

... risk, build higher-performing provider networks, and create a standout consumer experience in our ... As a Data Scientist II you will drive data science projects across multiple teams and domains. In ...

Oscar Health

Data Scientist II

Los Angeles, CA · Hybrid

$131K - $172K/yr

... risk, build higher-performing provider networks, and create a standout consumer experience in our ... As a Data Scientist II you will drive data science projects across multiple teams and domains. In ...

East West Bank

Financial Crimes Data Scientist

Pasadena, CA · On-site

$100K - $200K/yr

Financial Crimes Data Scientist specializing in the development, deployment, and optimization of in ... Develop risk-scoring, anomaly detection, predictive, and network analytics models using internal ...

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All JobsData Scientist Risk JobsData Scientist Risk Jobs in California

Data Scientist Risk information

See California salary details

$37K

$121.1K

$193.9K

How much do data scientist risk jobs pay per year?

As of Sep 12, 2026, the average yearly pay for data scientist risk 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 data scientist risk?

A Data Scientist Risk job involves using data analysis, machine learning, and statistical modeling to assess and mitigate financial, credit, or operational risks. These professionals work with large datasets to identify patterns, detect anomalies, and build predictive models that help organizations make informed decisions. They collaborate with risk management teams and stakeholders to develop strategies for minimizing potential losses while ensuring regulatory compliance. Strong analytical skills, proficiency in programming languages like Python or R, and knowledge of risk modeling techniques are essential for this role.

What types of projects or problems does a data scientist risk typically work on?

Data Scientist Risk professionals typically work on projects involving risk assessment, fraud detection, credit scoring, market risk analysis, and regulatory compliance. Their day-to-day responsibilities often include analyzing large datasets to identify patterns, building predictive models, and presenting insights to risk managers or executives to support risk mitigation strategies. You'll often collaborate with cross-functional teams including finance, IT, and compliance to develop innovative risk solutions and improve organizational decision-making. The work environment is dynamic and intellectually challenging, offering opportunities to continuously learn and make an impact in critical business areas.

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

To excel as a Data Scientist Risk, you need strong analytical skills, advanced knowledge of statistics, programming (typically in Python or R), and a relevant degree such as mathematics, finance, or data science. Familiarity with machine learning libraries, data visualization tools, and risk modeling software like SAS or SQL is commonly required, and certifications such as FRM or CFA are advantageous. Excellent problem-solving, critical thinking, and clear communication abilities are vital for interpreting complex data and presenting actionable insights to stakeholders. These competencies are crucial for accurately assessing risk, supporting decision-making, and ensuring regulatory compliance in fast-paced business environments.

What are the most commonly searched types of Data Scientist Risk jobs in California?

The most popular types of Data Scientist Risk jobs in California are:

What are popular job titles related to Data Scientist Risk jobs in California?

For Data Scientist Risk jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Scientist Risk jobs in California look for?

The top searched job categories for Data Scientist Risk jobs in California are:

What cities in California are hiring for Data Scientist Risk jobs?

Cities in California with the most Data Scientist Risk job openings:

Data Scientist Risk jobs near you
Infographic showing various Data Scientist Risk job openings in California as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $121,131 per year, or $58.2 per hour.

Staff Data Scientist - Fraud & Risk

San Francisco, CA • On-site

Socure
Software Development • 501 - 1,000 employees
Learn more about Socureexternal

$180K - $210K/yr

Full-time

Re-posted 9 days ago

Key responsibilities

  • Design, develop, and implement advanced deep learning models to address fraud and risk challenges.

  • Lead the end-to-end machine learning lifecycle, including data exploration, feature engineering, model training, evaluation, deployment, and monitoring.

  • Mentor peers and collaborate with cross-functional teams to define data requirements and drive insights.

Job description

Why Socure?
Socure is building the identity trust infrastructure for the digital economy - verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won't be your place. If you want to help build the future of identity with a team that holds a high bar for itself - keep reading.
About the Role
We are seeking a skilled and motivated Staff Data Scientist to join our Fraud & Risk Data Science team. As an advanced-level individual contributor, you will design, build, and optimize advanced DS/ML models that power our core fraud detection and risk management solutions. You will lead technical initiatives, mentor peers, and drive functional productivity and project success. You will work hands-on with advanced deep learning models, driving delivery of impactful solutions for fraud detection, risk management, and identity verification. This role requires deep technical expertise, strategic ownership, and a commitment to Socure's leadership principles, including continuous learning, effective communication, and accountability.
What You'll Do
  • Design, develop, and implement advanced deep learning models, including transformers, CNNs/RNNs, and graph learning algorithms, to address complex fraud and risk challenges.
  • Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
  • Lead the end-to-end machine learning lifecycle: data exploration, feature engineering, model training, evaluation, deployment, and monitoring in production environments.
  • Take ownership of project outcomes, data quality, and delivery timelines; proactively escalate issues and work collaboratively to resolve challenges.
  • Mentor and share knowledge with peers and junior data scientists, fostering a culture of experimentation, rapid iteration, and continuous learning.
  • Collaborate cross-functionally with Product, Engineering, and Risk teams to define data requirements and drive insights that guide strategic decisions.
  • Conduct in-depth research to explore new data sources and develop novel algorithms that advance the state of the art in fraud detection.
  • Present findings and recommendations to technical and executive stakeholders with clarity and influence.
  • Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
  • Model Socure's embedded leadership competencies: continuous learning, effective communication, accountability, team development, decision making, and managing change.
What You Bring
  • Master's or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field; or equivalent professional experience.
  • 8+ years of experience in data science, machine learning, or related fields, ideally in a high-growth tech or fintech environment.
  • Experience in fraud prevention, risk modeling, or identity verification.
  • Years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs/RNNs, and graph learning).
  • Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.
  • Strong proficiency in Python, SQL, and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
  • Deep understanding of machine learning algorithms, model evaluation techniques, and data pipeline development.
  • Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
  • Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus.
  • Demonstrated ability to proactively deliver complex outcomes, mentor others, and influence cross-functional decisions.
  • Excellent communication skills with the ability to translate complex data problems into actionable business insights for both technical and non-technical audiences.
  • Commitment to continuous learning, professional integrity, and high standards of business ethics.

Please note: we are unable to provide sponsorship now, or in the future.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
If you need an accommodation during any stage of the application or hiring process-including interview or onboarding support-please reach out to your Socure recruiting partner directly.
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