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Manager, Fraud Detection and Data Analytics

Fidelity Investments · Merrimack, NH · United States

Lead fraud detection strategies, analyzing real‑time data to safeguard financial transactions. Apply Python, SQL, and advanced analytics to uncover anomalies and mitigate cryptocurrency scams.

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Lead fraud detection strategies, analyzing real‑time data to safeguard financial transactions.

Apply Python, SQL, and advanced analytics to uncover anomalies and mitigate cryptocurrency scams.

Manager, Fraud Detection and Analytics

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

The Role

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.

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 fraud and scam schemes and implementing detection solutions to mitigate risk, using advanced analytics and data analysis tools.

Key responsibilities include:

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) and predictive statistics to perform advanced analytics and uncover actionable insights.

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, fraud/scams analytics, or crypto is a plus.

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

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.

The base salary range for this position is $97,000-185,000 USD per year.

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home.  These benefits include comprehensive health care coverage and emotional well‑being support, market‑leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career.  Note, the application window closes when the position is filled or unposted.

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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