Data Scientist (Fraud Analysis)

Wenger & Watson; California (MO); On-site; USD 80,000 - 110,000; Full time

Job summary

A leading company in data infrastructure and analytics is seeking a Data Science professional specializing in Fraud Analytics. The role involves utilizing data analytics tools to assess fraud trends, develop prevention strategies, and collaborate with various teams to enhance fraud prevention measures. Ideal candidates will have a strong background in data analytics, excellent communication skills, and a proactive approach to problem-solving.

Qualifications

• 3+ years of proven data analytics experience in fraud prevention or related fields.

Responsibilities

• Utilize data analytics tools to assess and generate fraud rules.
• Investigate suspicious activities and develop prevention strategies.
• Collaborate with cross-functional teams to enhance fraud prevention.

Skills

Data Analytics

Communication

Problem Solving

Education

Bachelor's degree in engineering, technology, computer science, or related field

Tools

Fraud Detection Software

Job description

Job Role: Data Science - Fraud Analytics

Location: New York, NY / San Jose, CA

Preferred Domain: Finance / Banking

Roles and Responsibilities:

1. Utilize data analytics tools and methodologies to conduct in-depth assessments and generate fraud rules and reports on fraud trends, including Merchant Fraud, first-party, and third-party fraud.
2. Investigate suspicious activities and transactions, determine root causes, and develop strategies and statistical models to prevent future occurrences.
3. Develop fraud rules on workflow systems.
4. Generate reports for ongoing monitoring of fraud events.
5. Prepare reports and presentations outlining fraud risks, incidents, and mitigation strategies for management review.
6. Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures.
7. Monitor industry trends, regulatory changes, and best practices to continually improve fraud prevention strategies.

Skills Required:

• Bachelor's degree in engineering, technology, computer science, or related field.
• 3+ years of proven data analytics experience in fraud prevention, risk management, or related fields.
• Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance.
• Excellent communication and presentation skills to convey complex information clearly and concisely.
• Detail-oriented with a proactive approach to problem-solving and risk mitigation.
• Ability to work collaboratively in a cross-functional team environment.

Additional Details:

• Seniority level: Mid-Senior level
• Employment type: Full-time
• Job function: Information Technology, Engineering, and Other
• Industries: Data Infrastructure and Analytics