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Temporary Fraud Data Scientist Jobs in California

BILL

Fraud Strategy Data Scientist

San Jose, CA · On-site

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve ...

BILL

Fraud Strategy Data Scientist

San Jose, CA · On-site

Minimum 3+ years of experience in end to end fraud risk control strategy experience within relevant industry experience in eCommerce, or online payments, leveraging data science/analytics to solve ...

Booz Allen Hamilton, Inc.

Data Scientist

Monterey, CA · On-site

$77K - $176K/yr

As a data scientist at Booz Allen, you can help turn these complex data sets into useful ... Across private and public sectors, from fraud detection to cancer research to national intelligence ...

Booz Allen Hamilton

Data Scientist

Monterey, CA

$77K - $176K/yr

As a data scientist at Booz Allen, you can help turn these complex data sets into useful ... Across private and public sectors, from fraud detection to cancer research to national intelligence ...

Mindlance

Data Scientist

San Francisco, CA · On-site

They are seeking a Data Scientist to develop predictive models in marketing, understand business ... The role involves using machine learning models for web content categorization and fraud detection.

Walmart

(USA) Staff, Data Scientist

Fremont, CA · On-site

$143K - $286K/yr

The global fraud data science team develops real-time and batch decisioning services using advanced machine learning and deep learning techniques to address fraud and risk within Walmart Inc. Focused ...

Walmart

(USA) Staff, Data Scientist

Sunnyvale, CA · On-site

$143K - $286K/yr

The global fraud data science team develops real-time and batch decisioning services using advanced machine learning and deep learning techniques to address fraud and risk within Walmart Inc. Focused ...

Walmart

(USA) Staff, Data Scientist

Milpitas, CA · On-site

$143K - $286K/yr

The global fraud data science team develops real-time and batch decisioning services using advanced machine learning and deep learning techniques to address fraud and risk within Walmart Inc. Focused ...

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Temporary Fraud Data Scientist information

What does a temporary fraud data scientist do?

A Temporary Fraud Data Scientist analyzes large datasets to detect and prevent fraudulent activities within a company, usually on a short-term or project-based contract. They use statistical models, machine learning, and data mining techniques to identify suspicious patterns and anomalies. Their work helps organizations minimize financial losses and improve security measures, often collaborating with other teams like IT, risk management, and compliance. Because the position is temporary, they are typically brought in to address urgent needs, such as investigating a recent spike in fraud or implementing new detection systems.

What are the key skills and qualifications needed to thrive as a temporary fraud data scientist, and why are they important?

To thrive as a Temporary Fraud Data Scientist, you need strong analytical skills, experience with statistical modeling, and a background in data science or a related field, often supported by a relevant degree. Proficiency in programming languages such as Python or R, knowledge of machine learning frameworks, and familiarity with fraud detection systems are typically required. Strong problem-solving abilities, attention to detail, and effective communication help you quickly adapt and collaborate during short-term assignments. These skills are crucial for rapidly identifying fraudulent activities, delivering actionable insights, and ensuring business integrity within limited timelines.

What are some common challenges faced by temporary fraud data scientists when joining an existing analytics team?

Temporary Fraud Data Scientists often face challenges such as quickly adapting to existing data infrastructure, understanding proprietary fraud detection models, and getting up to speed on the organization's specific fraud patterns. Because the role is temporary, there is a need to rapidly build relationships with cross-functional teams, such as compliance, IT, and operations, to access necessary data and insights. Effective communication and the ability to learn organizational processes swiftly are key to delivering impactful analyses within a limited timeframe.

What is the difference between Temporary Fraud Data Scientist vs Fraud Data Analyst?

AspectTemporary Fraud Data ScientistFraud Data Analyst
CredentialsDegree in Data Science, Statistics, or related field; experience with machine learningDegree in Data Analysis, Statistics, or related; proficiency in data tools
Work EnvironmentProject-based, short-term assignments, often in financial or e-commerce sectorsOngoing role within fraud prevention teams, often in finance or banking
Employer & Industry UsageFinancial institutions, e-commerce, insurance companiesBanking, credit card companies, online retailers

Temporary Fraud Data Scientists focus on developing models and algorithms to detect fraud, often on short-term projects. Fraud Data Analysts analyze data patterns to identify suspicious activity, typically in ongoing roles. Both roles require data analysis skills but differ in scope, tools, and project duration.

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

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

What cities in California are hiring for Temporary Fraud Data Scientist jobs?

Cities in California with the most Temporary Fraud Data Scientist job openings:

Temporary Fraud Data Scientist jobs near you

Fraud Data Analyst

Bright Mind Solutions LLC

Cupertino, CA • On-site

$85 - $90/hr

Contractor

Re-posted 14 days ago

Job description

****Local to Cupertino only***Must be local to Cupertino***
 
 

Citizens only

6 months 

full linkedin

Date of birth

NO FAKE RESUMES 

Job Title: Fraud Data Analyst
Company: Big Four Client
Location: Bay Area (CA)
Work Authorization: U.S. Citizen or Green Card Holder
 
Duration: 7+ Months
 
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.
 
If you are interested or have any references please share resume at mukul@brightmindsol.com