Senior Manager, Fraud Detection and Analytics

Fidelity Investments

$110K — $130K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of experience in data analytics, particularly in fraud detection or risk management.
  • Strong proficiency in Python and SQL for data analysis and automation.
  • Experience with large-scale datasets and modern data platforms.
  • Skilled in statistical analysis, visualization, and reporting tools.
  • Familiarity with fraud detection methodologies related to account compromise and scams.
  • Ability to convert complex data into clear insights for diverse audiences.
  • Strong communication and teamwork abilities.

Responsibilities

  • Analyze complex datasets to identify patterns in account takeover and fraud.
  • Extract actionable insights from large volumes of data using Python and SQL.
  • Evaluate and enhance vendor and internal tools for fraud detection.
  • Support efforts to identify organized fraud rings and coordinated attacks.
  • Communicate findings to influence fraud prevention strategies.
  • Collaborate with cross-functional teams to improve fraud detection models and reporting tools.
  • Contribute to the improvement of fraud analytics capabilities and operational effectiveness.

Benefits

  • Access to advanced analytics and fraud detection technologies.
  • Opportunity to work in a collaborative and cross-functional environment.
  • Focus on continuous improvement of fraud detection processes.
  • Engagement with diverse teams including data scientists and business stakeholders.
Full Job Description

Job Description:

Senior Manager, Fraud Detection and Analytics

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

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.

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

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