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Associate Data Scientist, Fraud Strategy

San Francisco, CA

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Salary not listed in the saved posting
Work setup
Working pattern needs review — work setup source
Exposure to feature engineering, predictive modeling, model monitoring, or experimentation Work Location San Francisco The above locations are eligible offices for this role. The locations have been determined to foster in-person collaboration with this role’s team or the related business lines. We utilize a hybrid work model, and our teams are in-office Tuesdays, Wednesdays, and Thursdays. In-person attendance is essential for this role’s success, and remote placement will not be considered. Happen Bank offers relocation, based on actual job level. Time Zone Requirements Local hours (PT) While the position will primarily work local hours, Happen Bank is headquartered in Pacific Time and our ideal candidate will be flexible working across time zones when necessary. Travel Requirements As needed travel to Happen Bank offices and/or other locations, as needed. Compensation The target base salary range for this position is 125,000-145,000. The base salary of the role will be determined by job-related knowledge, experience, education, skills, and location. Base salary is just one part of Happen Bank's Total Rewards package. You may also be eligible for long-term awards (equity) and an annual bonus (which is based on company performance, employee performance and eligible earnings). We’re creating new financial services solutions for our members based on fairness, simplicity, and heart, and we treat our employees the same way. We offer a competitive benefits package that includes medical, dental and vision plans for employees and their families, 401(k) match, health and wellness programs, flexible time off policies for salaried employees, up to 16 weeks paid parental leave and more. #LI-Hybrid #LI-AH1 Happen Bank is an equal opportunity employer and dedicated to diversity, equity, and inclusion in the workplace. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), gender, gender identity, gender expression, sexual orientation, age, marital status, veteran status, disability status, political views or activity, or other applicable legally protected characteristics. We believe that a variety of perspectives will make our teams and business stronger as we work together to transform the traditional banking system.
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What you’ll work on

Full posting

The Fraud and Data Science team uses internal and external data to detect, prevent, and mitigate fraud across Happen Bank.

  • Analyze large, complex datasets using SQL and Python to identify fraud patterns, emerging risks, and opportunities to improve decision-making

  • Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements

  • Monitor fraud trends, loss metrics, strategy performance, and key indicators, investigating anomalies and translating findings into actionable insights

From the employer’s posting
The Fraud and Data Science team uses internal and external data to detect, prevent, and mitigate fraud across Happen Bank. As an Associate Data Scientist, you’ll turn complex data into actionable insights, develop analytical solutions that strengthen fraud strategies, and partner across Fraud, Risk, Product, Technology, and Operations while building deeper technical and business expertise.
What You'll Do Analyze large, complex datasets using SQL and Python to identify fraud patterns, emerging risks, and opportunities to improve decision-making Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements
Analyze large, complex datasets using SQL and Python to identify fraud patterns, emerging risks, and opportunities to improve decision-making Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements Monitor fraud trends, loss metrics, strategy performance, and key indicators, investigating anomalies and translating findings into actionable insights
Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements Monitor fraud trends, loss metrics, strategy performance, and key indicators, investigating anomalies and translating findings into actionable insights Build and maintain reliable queries, dashboards, and reporting using established data and business intelligence standards

What you’ll bring

All qualifications

Core experience

  • 2+ years of experience in data science, fraud analytics, decision science, or a related analytical role
  • Experience in fraud, credit risk, financial services, e-commerce, or another high-volume digital environment
  • Bachelor's degree or higher, or equivalent combination of education and experience
  • Experience with Tableau or another business intelligence and visualization platform
  • Hands-on experience using SQL and a statistical programming language such as Python to work with large datasets and produce reproducible analysis
  • Ability to translate analytical findings into clear recommendations for technical and business audiences
Qualification wording
2+ years of experience in data science, fraud analytics, decision science, or a related analytical role
Experience in fraud, credit risk, financial services, e-commerce, or another high-volume digital environment
Bachelor's degree or higher, or equivalent combination of education and experience
Experience with Tableau or another business intelligence and visualization platform
Hands-on experience using SQL and a statistical programming language such as Python to work with large datasets and produce reproducible analysis
Ability to translate analytical findings into clear recommendations for technical and business audiences

Tools in this posting

  • Python
  • SQL
  • Tableau
Source — Tool mentions in context
What You'll Do - Analyze large, complex datasets using SQL and Python to identify fraud patterns, emerging risks, and opportunities to improve decision-making - Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements
- Bachelor's degree or higher, or equivalent combination of education and experience - Hands-on experience using SQL and a statistical programming language such as Python to work with large datasets and produce reproducible analysis - Working knowledge of statistical analysis, data visualization, and model or strategy performance measurement
- Experience in fraud, credit risk, financial services, e-commerce, or another high-volume digital environment - Experience with Tableau or another business intelligence and visualization platform - Exposure to feature engineering, predictive modeling, model monitoring, or experimentation

Job description

View original posting ↗

Current Employees of Happen Bank: Please apply via your internal Workday Account


Happen Bank (formerly LendingClub) is built around a simple purpose: to clear the way to help people turn intention into action, and action into financial progress. That means offering focused products, a frictionless mobile-first experience, and clear terms with no gotchas. Respect and fairness is part of our DNA, and that ideal shapes how we work, how we treat each other, and how we invest in our employees and our community. Join us in using data, bold thinking, and a commitment to innovation to help clear the way for millions of Americans to achieve more.


About the Role

The Fraud and Data Science team uses internal and external data to detect, prevent, and mitigate fraud across Happen Bank. As an Associate Data Scientist, you’ll turn complex data into actionable insights, develop analytical solutions that strengthen fraud strategies, and partner across Fraud, Risk, Product, Technology, and Operations while building deeper technical and business expertise.

What You'll Do

  • Analyze large, complex datasets using SQL and Python to identify fraud patterns, emerging risks, and opportunities to improve decision-making 
  • Support the development and implementation of fraud detection strategies, rules, and models based on data analysis and business requirements 
  • Monitor fraud trends, loss metrics, strategy performance, and key indicators, investigating anomalies and translating findings into actionable insights 
  • Build and maintain reliable queries, dashboards, and reporting using established data and business intelligence standards 
  • Evaluate new internal and external data sources, features, and analytical techniques for predictive value, data quality, and practical application 
  • Develop repeatable processes to monitor model and strategy performance, data accuracy, and changes in population behavior 
  • Partner with cross-functional teams to translate business questions into analytical approaches and support solutions from analysis through implementation 
  • Use AI-assisted tools where appropriate to accelerate exploration, coding, and documentation while validating outputs and protecting sensitive data 

About You

  • 2+ years of experience in data science, fraud analytics, decision science, or a related analytical role 
  • Bachelor's degree or higher, or equivalent combination of education and experience 
  • Hands-on experience using SQL and a statistical programming language such as Python to work with large datasets and produce reproducible analysis 
  • Working knowledge of statistical analysis, data visualization, and model or strategy performance measurement 
  • Ability to translate analytical findings into clear recommendations for technical and business audiences 
  • You take ownership of assigned work, ask thoughtful questions, and incorporate feedback to improve quality and outcomes 
  • You use sound judgment when handling sensitive data and applying new methods, balancing speed with accuracy, explainability, and risk 
  • You have practical familiarity with AI tools, understand their strengths and limitations, and are ready to apply that judgment to real-world analytical problems 
  • You collaborate with humility, adapt to changing priorities, and bring curiosity, integrity, and a problem-solving mindset

Nice to Have

  • Experience in fraud, credit risk, financial services, e-commerce, or another high-volume digital environment
  • Experience with Tableau or another business intelligence and visualization platform
  • Exposure to feature engineering, predictive modeling, model monitoring, or experimentation

Work Location  
San Francisco 
 
The above locations are eligible offices for this role. The locations have been determined to foster in-person collaboration with this role’s team or the related business lines. We utilize a hybrid work model, and our teams are in-office Tuesdays, Wednesdays, and Thursdays. In-person attendance is essential for this role’s success, and remote placement will not be considered. Happen Bank offers relocation, based on actual job level.  
 
Time Zone Requirements  
Local hours (PT) 
 
While the position will primarily work local hours, Happen Bank is headquartered in Pacific Time and our ideal candidate will be flexible working across time zones when necessary. 
 
Travel Requirements  
As needed travel to Happen Bank offices and/or other locations, as needed.  
 
Compensation  
The target base salary range for this position is 125,000-145,000. The base salary of the role will be determined by job-related knowledge, experience, education, skills, and location. Base salary is just one part of Happen Bank's Total Rewards package. You may also be eligible for long-term awards (equity) and an annual bonus (which is based on company performance, employee performance and eligible earnings). 
 
We’re creating new financial services solutions for our members based on fairness, simplicity, and heart, and we treat our employees the same way. We offer a competitive benefits package that includes medical, dental and vision plans for employees and their families, 401(k) match, health and wellness programs, flexible time off policies for salaried employees, up to 16 weeks paid parental leave and more.  
 
#LI-Hybrid 
#LI-AH1 


Happen Bank is an equal opportunity employer and dedicated to diversity, equity, and inclusion in the workplace. We do not discriminate on the basis of race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), gender, gender identity, gender expression, sexual orientation, age, marital status, veteran status, disability status, political views or activity, or other applicable legally protected characteristics. We believe that a variety of perspectives will make our teams and business stronger as we work together to transform the traditional banking system. 

 

We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, please contact us at interviewaccommodations@happen.com. 


 

Notice on AI Tool Use 

 

For select roles and locations, candidate interviews may be recorded, transcribed and summarized by tools such as artificial intelligence (AI) to assist our hiring managers with the application process.


You will have the opportunity to opt out of recording, transcription, and summarization prior to any scheduled interviews. We will not discriminate against you if you choose to opt out.


During the interview, we will collect the following categories of personal information from or about you: contact information, identifiers, professional and employment-related information, sensory information (audio/video recording), and any other categories of personal information you choose to share with us.  We will use this information to evaluate your application for employment.

 

We will only share your interview, transcription, or summary with persons whose expertise or technology is necessary to process your application, evaluate your fitness for a position, and administer or support the tool. We will not sell your personal information or disclose it to any third party for their marketing purposes.  For more information about how we will handle your personal information, please refer to our Privacy Disclosure.


We will delete any recording of your interview promptly but in no event later than 30 days after making a hiring decision.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Pay

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Location & working pattern

San Francisco, CA

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Status in our records
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First seen by us
Sep 27, 2026
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3
Last seen by us
Oct 9, 2026

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