Senior Manager, Advanced Data Analytics and Insights

Fidelity • Merrimack, NH

19h • Hybrid

About The Position

Senior Manager, Fraud Detection and Analytics Fraud Risk & Control The Role The Fraud Risk and Control (FRC) Detection Team is responsible for identifying and mitigating fraudulent activity, focusing on unauthorized account access and suspicious behavior. The team uses a combination of vendor technologies and internally developed models to enable real-time detection and intervention across the customer lifecycle. As a Senior Manager, Fraud Detection and Analytics, you will collaborate with data scientists, fraud strategists, and business stakeholders to support and enhance real-time fraud detection strategies. Your work will focus on uncovering patterns related to account takeovers, and coordinated fraud attacks using advanced analytics and large-scale data Analyze complex datasets to detect patterns and trends related to account takeover and scam-related fraud. Use Python, SQL, and other analytical tools to extract actionable insights from large volumes of data. Evaluate and optimize vendor and internal tools to improve detection of fraudulent behaviors across digital experiences. Support anomaly detection efforts to identify organized fraud rings and coordinated attacks. Communicate findings clearly to influence stakeholders and guide fraud prevention strategies. Partner with cross-functional teams to develop and refine fraud detection models, dashboards, and reporting tools. Contribute to the continuous improvement of fraud analytics capabilities and operational effectiveness. The Expertise and Skills You Bring 7+ years of experience in data analytics, preferably within fraud detection, risk management, or cybersecurity. Strong proficiency in Python and SQL for data analysis and automation. Experience working with large-scale datasets and modern data platforms. Skilled in using analytics tools for statistical analysis, visualization, and reporting. Familiarity with fraud detection methodologies, especially related to account compromise and scams. Ability to translate complex data into clear, actionable insights for technical and non-technical audiences. Strong communication and collaboration skills to work effectively across teams. Experience in anomaly detection or behavioral analytics is a plus. Note: Fidelity will not provide immigration sponsorship for this position. Certifications: Category: Data Analytics and Insights Most roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M-F) in a Fidelity office. This does not apply to Remote or fully Onsite roles. Some roles may have unique onsite requirements. Please consult with your recruiter for the specific expectations for this position. 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.

Requirements

• 7+ years of experience in data analytics, preferably within fraud detection, risk management, or cybersecurity.
• Strong proficiency in Python and SQL for data analysis and automation.
• Experience working with large-scale datasets and modern data platforms.
• Skilled in using analytics tools for statistical analysis, visualization, and reporting.
• Familiarity with fraud detection methodologies, especially related to account compromise and scams.
• Ability to translate complex data into clear, actionable insights for technical and non-technical audiences.
• Strong communication and collaboration skills to work effectively across teams.

Nice To Haves

• Experience in anomaly detection or behavioral analytics is a plus.

Responsibilities

• Analyze complex datasets to detect patterns and trends related to account takeover and scam-related fraud.
• Use Python, SQL, and other analytical tools to extract actionable insights from large volumes of data.
• Evaluate and optimize vendor and internal tools to improve detection of fraudulent behaviors across digital experiences.
• Support anomaly detection efforts to identify organized fraud rings and coordinated attacks.
• Communicate findings clearly to influence stakeholders and guide fraud prevention strategies.
• Partner with cross-functional teams to develop and refine fraud detection models, dashboards, and reporting tools.
• Contribute to the continuous improvement of fraud analytics capabilities and operational effectiveness.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 101-250 employees