Digital Risk Jobs in Lake Mary, FL (NOW HIRING)

We're looking for a highly experienced and meticulous Network and Financial Risk
Analyst with a strong background in financial controls with a strong background in
financial controls, and digital forensics to join our team. The ideal candidate is strategic
thinker who can proactively prevent, detect, and resolve complex fraud schemes while
ensuring our systems and processes meet the highest standards for protecting sensitive
data.
Complexity:
Intermediate professional level role. Develop security solutions for medium to
high complex assignments. Works on multiple projects as a team member and may also
lead systems related. May coach junior level technical staff.
Develops, evaluates and maintains systems that help detect and prevent suspicious
transactions from being run and tested within the payment application.
Requires technical expertise in risk management tools, forensics (gathering of evidence,
presentation, chain of custody, etc.), combined management tools, forensics (gathering of
evidence, presentation, chain of custody, etc.) with knowledge of industry best practices
and procedures.
Assists in the development and implementation of financial controls that will deter and
prevent fraudulent activity.
Prepares status reports on security matters and develops security risk analysis scenarios
and response procedures regarding suspected payment card and banking fraudulent transactions.
Responsibilities
Lead and conduct in-depth investigations into suspected payment card fraud and
other financial crimes, from initial detection to final resolution.
Utilize advanced digital forensic techniques to acquire, preserve, and analyze digital
evidence from various sources to support investigations and root cause analysis.
Monitor and analyze transaction data, user behavior, and security alerts from SIEM
("Security Information and Event Management") and fraud detection systems to
identify suspicious patterns and indicators of compromise.
Implement a monitoring system to identify at a minimum:
Unusual spikes in failed payment transaction attempts.
High volume of low-value transactions from the same IP or device on single
credit cards.
Multiple transactions in quick succession utilizing different credit cards but
originating from the same IP, device fingerprint, or session ID.
Perform Log & SIEM Analysis for web and payment logs to detect at a minimum:
Burst patterns.
Consistent failed authorizations.
Repeated use of credit card data.
Enable alerting on anomalies such as:
Transaction volume per minute/hour.
Failure rate thresholds.
Collaborate with internal and external teams, including legal, compliance, and law
enforcement, to manage investigation cases and provide expert testimony or
detailed reports as needed or required.
Conduct forensic readiness assessments and contribute to the development of the
incident response plan to ensure the business enterprise can effectively respond to
a data breach.
Mentor junior analysts and stay current with the latest fraud tactics, cyber threats,
and security technologies.
Requirements
8-10 years of progressive experience in cybersecurity, with a focus on payment
fraud detection, resolution, and digital forensics.
Demonstrated expertise in security best practices, risk analysis approaches and
their practical application.
Familiarity with ISO, CIS, NIST, CSF and SCF frameworks and security controls.
Proven experience with forensic tools and applications (e.g., EnCase, FTK, or
similar).
Strong analytical skills, with a track record of using data analysis tools (e.g., SQL,
Python, other scripting languages) to investigate complex financial fraud schemes.
Excellent written and verbal communication skills, capable of producing detailed
reports and presenting findings to technical and non-technical audiences, including
executive leadership.
Certifications such as Certified Fraud Examiner (CFE), Certified Payments
Professional (CPP), and Certified Anti-Money Laundering Specialist (CAMS) are
highly preferred.
Bachelor's or Master's degree in Cybersecurity, Computer Science, or a related
field.