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Manager, Fraud Detection and Analytics

Role overview

Qualifications

  • Bachelor's with 5 plus years or Master's with 3 plus years of experience in data analytics, preferably in fraud detection, cybersecurity, or risk domains
  • Strong proficiency in Python and SQL for data analysis and automation
  • Experience working with large-scale datasets and analytical platforms
  • Skilled in using analytics tools (e.g., dashboards, statistical packages, data visualization platforms) to perform advanced analytics and uncover actionable insights

Responsibilities

  • Analyze complex datasets to identify risk signals related to fraudulent debit card transactions
  • Use Python, SQL, and analytical tools to analyze large, complex datasets and extract actionable insights
  • Implement fraud detection strategies in a real-time fraud decisioning engine
  • Support anomaly detection efforts to identify coordinated fraud attacks and organized fraud rings

Key facts

Hard skills

Other skills

  • Communication
  • Collaboration

About the company

Fidelity Investments logo

Fidelity Investments

Financial Services

Fidelity’s mission is to strengthen the financial well-being of our customers and deliver better outcomes for the clients and businesses we serve. Fidelity’s strength comes from the scale of our diversified, market-leading financial services businesses that serve individuals, families, employers, wealth management firms, and institutions. With assets under administration of $15.0 trillion, including discretionary assets of $5.9 trillion as of March 31, 2025, we focus on meeting the unique needs of a broad and growing customer base. Privately held for 78 years, Fidelity employs more than 77,000 associates across the United States, Ireland, and India. For our Terms and Conditions, please visit http://go.fidelity.com/LIterms

Company details

IndustryFinancial Services
Company size10,001+

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Job description

Job Description:

Note: Fidelity will not provide immigration sponsorship for this position.

The Role

In this role, you will work closely with data scientists, fraud strategists, and business stakeholders to support real-time fraud detection and prevention strategies. Your work will focus on identifying payment card fraud schemes and implementing detection solutions to mitigate risk, using advanced analytics and data analysis tools.

Key Responsibilities:

  • Analyze complex datasets to identify risk signals related to fraudulent debit card transactions.
  • Use Python, SQL, and analytical tools to analyze large, complex datasets and extract actionable insights.
  • Implement fraud detection strategies in a real-time fraud decisioning engine.
  • Support anomaly detection efforts to identify coordinated fraud attacks and organized fraud rings.
  • Communicate insights clearly and effectively to influence stakeholders and drive product changes.
  • Collaborate across business units to drive data-informed strategies for fraud detection.
  • Contribute to the continuous improvement of the fraud detection program, through rule and model refinement, fraud hunting, and data discovery.

The Expertise and Skills You Bring

  • Bachelor's with 5 plus years or Master's with 3 plus years of experience in data analytics, preferably in fraud detection, cybersecurity, or risk domains.
  • Strong proficiency in Python and SQL for data analysis and automation.
  • Experience working with large-scale datasets and analytical platforms.
  • Skilled in using analytics tools (e.g., dashboards, statistical packages, data visualization platforms) to perform advanced analytics and uncover actionable insights.
  • Familiarity with payment card fraud detection and risk management.
  • Ability to translate complex data into clear, actionable insights.
  • Strong communication and collaboration skills to work across teams and influence decisions.
  • Experience in anomaly detection or fraud analytics is a plus.

The Team

The Fraud Detection Analytics Team is responsible for ensuring that fraudulent events—such as account logins, account openings, and payment attempts—occurring on Fidelity’s platform are detected and mitigated in a timely manner. The team leverages a combination of vendor and internally developed tools and models to enable real-time detection and interdiction at various stages of the customer lifecycle.

Fidelity’s Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.

Certifications:

Category:

Data Analytics and Insights

Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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