Data Analyst - Forensics, Technology, Investigations & Discovery

BRG•Washington, DC

1d•$90,000 - $150,000

About The Position

BRG is seeking a Data Analyst for its Forensics, Technology, Investigations & Discovery (FTID) practice, which works in forensic accounting and global investigations, discovery and forensic technology, M&A and private equity disputes, and cybersecurity and investigations. The practice is seeking a Senior Associate who can demonstrate substantial knowledge or a record of success as an individual contributor or team leader in fraud risk, fraud prevention and detection, and/or data analytics. Depending on qualifications and experience, the job title may be Senior Associate or Consultant. The role applies data analytics and anti-fraud expertise to client engagements. Relevant technical areas include SQL, Python or R, data science, supervised and unsupervised machine learning, social network analysis, big data tools such as Hadoop and PySpark, cloud computing, cloud machine-learning tools, fraud detection rules and models, and data visualization. The role also evaluates tools and products that can enhance risk detection and prevention. The successful candidate will help identify and address client needs, develop and prioritize anti-fraud strategies, analytics, models, and operations, manage engagement teams and competing priorities, and communicate with stakeholders across business, risk, compliance, operations, technology, and analytics. The role includes working with client management and staff to gather information and perform services; presenting complex ideas; managing engagement documents and project economics; giving timely feedback; and keeping leadership informed while providing direction to junior staff. Candidates must be able to verify their legal right to work in the United States without company sponsorship. The stated salary range is $90,000–$150,000 per year.

Requirements

Bachelor's degree in Management Information Systems (MIS), Engineering, Accounting, Computer and Information Science, Mathematics, Finance, Economics, Statistics, or Data Processing/Analytics/Science.
At least three years of professional experience in regulatory investigations, internal investigations, and compliance remediation work.
Ability to verify legal authorization to work in the United States without company sponsorship.
Knowledge of SQL, Python or R, data science, supervised and unsupervised machine learning, and social network analysis.
Experience with big data tools such as Hadoop and PySpark, cloud computing, and cloud machine-learning tools.
Knowledge of anti-fraud business domains in e-commerce, payments, healthcare, and banking.
Ability to develop fraud detection rules and/or models deployed in systems such as Actimize, FICO Falcon, SAS Fraud Management, or other platforms.
Experience with data visualization tools such as Tableau, Spotfire, or QlikView.
Ability to manage engagements, communicate with stakeholders, work effectively with clients, and provide direction and feedback.

Nice To Haves

Experience in a global network of professional services firms.
Database or programming certifications, such as Oracle, Microsoft SQL Server, Azure Fundamentals, Certified Associate in Python Programming, Certified Kubernetes Administrator, Sun Certified Java Programmer, Microsoft Certified: DevOps Engineer Expert, or Azure AI Engineer Associate.
CPA and/or PMI certification.
Certified Fraud Examiner (CFE) certification is a plus.

Responsibilities

Apply data analytics, fraud risk, fraud prevention, and fraud detection expertise to client engagements.
Develop and prioritize anti-fraud strategies, analytics, models, and operations.
Use relevant data science, programming, machine-learning, big-data, cloud, fraud-modeling, and visualization capabilities.
Evaluate new tools and products that enhance risk detection and prevention.
Manage engagement teams and competing priorities in a fast-paced, cross-functional environment.
Communicate with business, risk, compliance, operations, technology, and analytics stakeholders.
Build positive client relationships and work with client management and staff at all levels to gather information and perform services.
Use presentation materials to communicate complex ideas to clients and internal staff.
Manage engagements, prepare concise and accurate documents, and maintain project economics while adapting to unanticipated issues.
Provide timely, candid, and meaningful feedback.
Keep leadership informed of progress and issues, answer questions, and provide direction to more junior staff.