A career in our Investigative Analytics practice, within Forensics Technology services, will provide you with the opportunity to help our clients protect their business in today’s evolving landscape by applying advanced and strategic approaches to information management. We focus on assisting organisations manage vast amounts of electronic data and navigate the legal and business processes demanded by critical events which includes litigation, regulatory requests and internal investigations. Our team helps design and build investigation support systems for our clients that work with, review, and provide insights of the data under investigation without the need for complex data analysis skills and without the risk of damaging the underlying evidence.

Responsibilities

As a Senior Manager, you’ll work as part of a team of problem solvers with extensive consulting and industry experience, helping our clients solve their complex business issues from strategy to execution. Specific responsibilities include but are not limited to:

• Proactively assist in the management of a portfolio of clients, while reporting to Directors and above
• Be involved in the financial management of clients
• Be actively involved in business development activities to help identify and research opportunities on new/existing clients
• Develop project strategies to solve complex technical challenges for our clients
• Manage and deliver large projects by developing the project team, assessing engagement risks throughout, driving conclusions, and reviewing / challenging the output produced by the team
• Shape and deliver projects to meet and exceed the expectations of our clients and our own quality criteria
• Train, coach, and supervise team members
• Continue to develop internal relationships and developing your PwC brand

Additional Responsibilities:

Fraud Analytics Managers will be part of a team with extensive consulting/industry experience & help solve complex problems from strategy to execution including advising clients on analytics-driven fraud prevention & detection strategies, developing & implementing effective fraud strategies to mitigate losses while establishing a balance between risk & customer experience, & assisting in client financial management & business development to help identify opportunities on new/existing clients.

Job Requirements and Preferences:

Basic Qualifications:

Minimum Degree Required:
Bachelor Degree

Minimum Years of Experience:
7 year(s)

Preferred Qualifications:

Degree Preferred:
Bachelor Degree

Preferred Fields of Study:
Management Information Systems, Engineering, Accounting, Computer and Information Science, Mathematics, Finance, Economics, Statistics, Data Processing/Analytics/Science

Certification(s) Preferred:
Database and programming certifications, such as Oracle, MS SQL Server; CPA; and/or PMI. Certified Fraud Examiner is a plus.

Preferred Knowledge/Skills:
Demonstrates intimate level of ability and/or proven record of success managing fraud risk, fraud prevention and detection, and/or data analytics, preferably for a global network of professional services firms, including several of the following areas:

• Leveraging advanced knowledge of SQL, Python or R, Data science skills & a knowledge of supervised and unsupervised machine learning, & social network analysis;
• Demonstrating experience with big data tools such as Hadoop & cloud computing, such as PySpark, and cloud machine learning tools; 
• Leveraging thorough anti-fraud business domain knowledge in the ecommerce, payments, healthcare, and banking industries;
• Developing fraud detection rules and/or models deployed in systems such as Actimize, FICO Falcon, SAS Fraud Management, or other platforms;
• Demonstrating experience with data visualization tools such as Tableau, Spotfire, or QlikView; and,
• Evaluating new tools and products that enhance risk detection and prevention. Demonstrates intimate abilities and/or proven record of success as a team leader by: 
• Leveraging advanced knowledge of SQL, Python or R, Data science skills & a knowledge of supervised and unsupervised machine learning, & social network analysis;
• Demonstrating experience with big data tools such as Hadoop & cloud computing, such as PySpark, and cloud machine learning tools; 
• Leveraging thorough anti-fraud business domain knowledge in the ecommerce, payments, healthcare, and banking industries;
• Developing fraud detection rules and/or models deployed in systems such as Actimize, FICO Falcon, SAS Fraud Management, or other platforms;
• Demonstrating experience with data visualization tools such as Tableau, Spotfire, or QlikView; and,
• Evaluating new tools and products that enhance risk detection and prevention.
• Applying subject matter specialization to the development and prioritization of anti-fraud strategies, analytics, models, and operations;
• Managing multiple engagement teams and competing priorities in a rapidly growing, cross-functional, fast-paced, interactive, results-based team environment;
• Managing communication with business, risk, compliance, operations, technology, and analytics stakeholders on client engagements;
• Fostering positive working relationships with clients & working effectively with client management and staff at all levels to gather information and perform services, & identify and address client needs;
• Displaying thorough written/verbal communication skills, & using presentation specialization to convey complex ideas to client & internal staff;
• Managing resource requirements, project workflow, budgets, billing & collections; and,
• Leading/training teams, coaching staff including providing timely meaningful written and verbal feedback and creating an atmosphere of trust, and seeking diverse views to encourage improvement and innovation.