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Software Engineer Fraud Detection Jobs in Santa Rosa, CA

Kodiak

Software Engineer, Embedded

Bodega Bay, CA

$150K - $210K/yr

Collaborate with software engineering on architecture, optimizations and reviews ... Contribute to hardware specifications to ensure test coverage and fault detection * Participate in ...

Apple

Cloud Network Software Engineer

Bodega Bay, CA

$184K - $324K/yr

Description As a Cloud Network Software Engineer you will be responsible for the cloud network ... incident detection and resolution times. Deliver on a sustainable incident response practices ...

Doxel

Senior Backend Software Engineer

Bodega Bay, CA

$145K - $191K/yr

We have classic computer vision, deep learning ML object detection, a low-latency 3D three.js web ... Our software is trusted by Shell Oil, Genentech, HCA healthcare, Kaiser, Turner, Layton and several ...

Block

Head of Product, Trust (Risk/Identity)

Bodega Bay, CA · On-site

$276K - $289K/yr

Drive execution across multiple functions and organizations including Product, Engineering ... Familiarity with ML/AI-powered risk and fraud detection systems * Experience with identity ...

Poppy Bank

BSA Compliance Analyst

Santa Rosa, CA

Detect, respond, and report Elder Financial Abuse to the appropriate authorities within the ... Proficiency with computer programs including fraud identification and AML software * Organize ...

New

Poppy Bank

BSA Compliance Analyst

Santa Rosa, CA · On-site

Detect, respond, and report Elder Financial Abuse to the appropriate authorities within the ... Proficiency with computer programs including fraud identification and AML software * Organize ...

New

AeroVironment, Inc.

Systems Engineer II

Petaluma, CA · On-site

$82K - $125K/yr

Definition of system Build in Test for Fault Detection, Isolation, Recovery * Definition of ground ... Familiarity with office software and computer-based productivity tools * The ideal candidate will ...

AeroVironment

Systems Engineer II

Petaluma, CA · On-site

$82K - $125K/yr

Definition of system Build in Test for Fault Detection, Isolation, Recovery * Definition of ground ... Familiarity with office software and computer-based productivity tools * The ideal candidate will ...

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All JobsSoftware Engineer Fraud Detection JobsSoftware Engineer Fraud Detection Jobs in Santa Rosa, CA

Software Engineer Fraud Detection information

See Santa Rosa, CA salary details

$26.2K

$114.7K

$206.6K

How much do software engineer fraud detection jobs pay per year?

As of Aug 30, 2026, the average yearly pay for software engineer fraud detection in Santa Rosa, CA is $114,650.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,100.00 and $131,200.00 per year, depending on experience, location, and employer.

What does a software engineer fraud detection do?

A Software Engineer in Fraud Detection designs and develops systems to identify and prevent fraudulent activities within digital platforms, such as banking or e-commerce environments. They build algorithms to analyze user behavior, detect anomalies, and flag suspicious transactions in real time. Their work often involves machine learning, big data analysis, and close collaboration with data scientists and security teams to continuously improve fraud detection accuracy. These engineers play a key role in protecting businesses and customers from financial loss and cybercrime.

How does a software engineer fraud detection typically collaborate with data scientists and analysts to identify fraudulent activity?

Software Engineers in Fraud Detection work closely with data scientists and analysts to build, refine, and deploy systems that detect and prevent fraud. While data scientists may develop models and identify patterns from large datasets, engineers are responsible for integrating these models into scalable, real-time systems within the company's technology stack. Regular communication and joint problem-solving are essential, as engineers must understand the logic behind models and analysts' findings to ensure accurate implementation and continuous improvement. This collaborative environment helps create robust fraud detection mechanisms that adapt to evolving threats.

What are the key skills and qualifications needed to thrive as a software engineer fraud detection, and why are they important?

To thrive as a Software Engineer in Fraud Detection, strong programming skills (such as Python, Java, or Scala), a solid understanding of algorithms, data structures, and experience with machine learning or statistical analysis are generally required, often supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), real-time analytics systems, and fraud detection tools or frameworks is typically expected. Analytical thinking, problem-solving abilities, and effective communication are key soft skills that differentiate top performers in this field. These skills are crucial for developing robust systems that can quickly identify and prevent fraudulent activities, protecting both users and organizations.

What is the difference between Software Engineer Fraud Detection vs Data Scientist Fraud Detection?

AspectSoftware Engineer Fraud DetectionData Scientist Fraud Detection
Required CredentialsBachelor's in CS or related field, programming skillsBachelor's or higher in CS, Statistics, or Data Science
Work EnvironmentDevelops fraud detection systems, writes code, implements algorithmsAnalyzes data, builds models, interprets results
Employer & Industry UsageFinancial institutions, fintech, e-commerceFinancial services, tech companies, insurance
Common Search & ComparisonFocuses on software development for fraud detectionFocuses on data analysis and modeling for fraud detection

While both roles work in fraud detection, Software Engineer Fraud Detection primarily develops and maintains detection systems through coding, whereas Data Scientist Fraud Detection analyzes data and builds models to identify fraudulent activity. Both roles often collaborate but differ in their core focus and skill sets.

What are popular job titles related to Software Engineer Fraud Detection jobs in Santa Rosa, CA?

For Software Engineer Fraud Detection jobs in Santa Rosa, CA, the most frequently searched job titles are:

What job categories do people searching Software Engineer Fraud Detection jobs in Santa Rosa, CA look for?

The top searched job categories for Software Engineer Fraud Detection jobs in Santa Rosa, CA are:

What cities near Santa Rosa, CA are hiring for Software Engineer Fraud Detection jobs?

Cities near Santa Rosa, CA with the most Software Engineer Fraud Detection job openings:

Software Engineer Fraud Detection jobs near you

Fraud Data Analyst

Bodega Bay, CA • On-site

Cloud think technologies LLC
See more jobs at Cloud think technologies LLCexternal

Contractor

Re-posted 7 days ago

Job description

Must have: Development to design and implement fraud monitoring solutions

and fraud prevention strategies.
◦ Analyze large datasets to identify trends, patterns, and anomalies related to gift
card fraud.
◦ Develop and maintain dashboards and reports that monitors suspicious activities
trends.
◦ Create and track fraud KPIs to measure the effectiveness of fraud prevention
strategies.
◦ Proactively identify emerging gift card fraud schemes and develop strategies to
mitigate them.
◦ Collaborate with other fraud analysts, data scientists, and engineers to develop
fraud prevention tools, systems and products."

Overview

We are seeking an experienced Fraud Data Analyst specializing in gift card fraud to join our team in the Bay Area. In this critical role, you will leverage your advanced PySpark expertise (6–9 years) and strong analytical skills to develop and implement robust fraud monitoring solutions that protect our customer's business. You will work cross-functionally with Fraud, Legal, Operations, Product, and Business Development teams to proactively detect, analyze, and mitigate complex gift card fraud schemes.

Key Responsibilities

  • Collaborate with cross-functional teams including Fraud, Legal, Operations, Product, and Business Development to design and implement scalable fraud monitoring solutions and dynamic fraud prevention strategies.
  • Analyze large-scale transactional and behavioral datasets using advanced PySpark to uncover trends, patterns, and emerging anomalies related to gift card fraud.
  • Develop and maintain insightful dashboards and regular reports to monitor suspicious activity trends and fraudulent behaviors.
  • Create and track fraud-specific Key Performance Indicators (KPIs) to measure and optimize the effectiveness of fraud prevention initiatives.
  • Proactively identify and assess new and emerging gift card fraud schemes, recommending and executing risk mitigation strategies.
  • Partner with other fraud analysts, data scientists, and engineers to build and refine fraud prevention tools, machine learning models, and monitoring systems.
  • Communicate analytical findings and recommendations clearly to both technical and non-technical stakeholders.

Required Qualifications:

  • Advanced-level proficiency in PySpark (6–9 years of hands-on experience), including large-scale data processing and ETL workflows.
  • Demonstrated experience in fraud detection, ideally with a focus on gift card fraud.
  • Strong skills in data analysis, pattern recognition, and statistical modeling.
  • Professional experience collaborating with cross-functional business and technical teams.
  • Excellent written and verbal communication skills.

Preferred Qualifications:

  • Proficiency in SQL and Hadoop for data extraction, manipulation, and analytics.
  • Experience developing dashboards and reports using BI tools (e.g., Tableau, PowerBI).
  • Familiarity with building or evaluating machine learning models for fraud detection.

Description:

The services You will provide the Deloitte project team: As a Data Analytics Contractor, you will analyze and interpret complex data sets to provide actionable insights and support decision-making processes. Collect, process, and analyze large datasets to identify trends, patterns, and insights. Develop and maintain data models, dashboards, and reports to visualize data findings. Utilize statistical and analytical tools to perform data analysis and generate insights. Collaborate with project teams to understand data requirements and deliver relevant analytical solutions. Ensure data accuracy and integrity by performing data validation and quality checks.

Enable Skills-Based Hiring

No

Primary Skill Required for the Role

 

Pyspark

Level Required for Primary Skill

 

Advanced (6-9 years’ experience)

Additional Details for Role

 

Data Analyst
"◦ Collaborate with cross-functional teams such as Fraud, Legal, Operations, Product
and Business