Senior Data Forensics & Investigations Analyst

BRG; New York (NY); On-site; USD 90,000 - 150,000; Full time

Job summary

BRG is expanding its FTID practice and seeking a Senior Associate or Consultant to lead fraud risk, prevention, and detection initiatives with a global network. The role emphasizes data analytics, model development, and cross-functional client collaboration across industries like e-commerce, payments, healthcare, and banking.

The ideal candidate will bring a strong background in data science, SQL, Python/R, and hands-on experience with big data tools, visualization platforms, and fraud

Qualifications

• Bachelor's degree in MIS, Engineering, Accounting, Computer and Information Science, Mathematics, Finance, Economics, Statistics, Data Processing/Analytics/Science; and
• Minimum of three (3) years of professional experience working in regulatory investigations, internal investigations, and compliance remediation work.

Responsibilities

• Develop anti-fraud analytics, models, and operations.
• Manage engagement teams and priorities in a fast-paced environment.
• Communicate with business, risk, compliance, operations, technology, and analytics stakeholders on client engagements.
• Foster positive working relationships with clients and client staff at all levels.
• Provide candid, timely feedback and keep leadership informed of progress and issues.

Skills

SQL

Python

R

Data science

Machine learning

Data visualization

Communication

Education

Bachelor's degree in MIS/Engineering/Accounting/CS/Data Science

Tools

Hadoop

PySpark

Tableau

Spotfire

QlikView

Actimize

FICO Falcon

SAS Fraud Management

Azure

Job description

BRG is expanding its FTID practice and seeking a Senior Associate or Consultant to lead fraud risk, prevention, and detection initiatives with a global network. The role emphasizes data analytics, model development, and cross-functional client collaboration across industries like e-commerce, payments, healthcare, and banking.

The ideal candidate will bring a strong background in data science, SQL, Python/R, and hands-on experience with big data tools, visualization platforms, and fraud