PwC Fraud Engineer and Implementation Specialist - Senior Manager in New York, New York
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.
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 :
A Fraud Engineer/Implementation Manager will join the team with consulting/industry experience to help clients solve complex problems from strategy to execution including assisting with analytics-driven fraud prevention & detection strategies, developing & implementing effective fraud strategies to mitigate losses while establishing a balance between risk & customer experience, & business development to help identify opportunities on new/existing clients.
Job Requirements and Preferences :
Basic Qualifications :
Minimum Degree Required :
Minimum Years of Experience :
Preferred Qualifications :
Degree Preferred :
Preferred Fields of Study :
Management Information Systems, Computer and Information Science, Engineering, Mathematics, Statistics
Preferred Knowledge/Skills :
Demonstrates intimate knowledge and/or proven record of success in managerial roles involving, forensic technology, anti-fraud technology solutions, and/or fraud prevention/ authentication solutions, or developing and engineering data stores for fraud analytics, preferably for a global network of professional services firms, including the following areas:
Managing relational and NoSQL Databases, especially utilizing one or more of the following environments including: Python, Hadoop, Apache Spark, MongoDB or other JSON databases, Actimize, Microsoft SQL, Oracle, Informatic, or VBA, and Apache Kafka, data engineering, data integration, software engineering and software implementation;
Managing and utilizing Machine Learning analytics;
Managing ERPs, especially multiple business and accounting cycles, financial reporting activities, and data models;
Understanding industry-specific business processes and accounting practices, such as fraud technology professional services, fraud technology vendors, Banking, eCommerce, Mobile Telecom, technology or other industries; and,
Consulting or helping to manage industry-related data analytics and/or financial management, emphasizing multiple business and accounting cycles.
Demonstrates intimate abilities and/or proven record of success in forensic technology, integrating and deploying anti-fraud technology solutions, and/or fraud prevention/ authentication solutions, or developing and engineering data stores for fraud analytics, preferably for a global network of professional services firms, including the following areas:
Managing multiple engagement teams and competing priorities in a rapidly growing, cross-functional, fast-paced, interactive, results-based team environment;
Creating, managing, and utilizing machine learning analytics, high performance relational and NoSQL databases such as Microsoft SQL Server, Oracle, Microsoft Access, OLAP, Hive, Python, Hadoop, Apache Spark, MongoDB or other JSON databases;
Gathering, standardizing, and analyzing voluminous transactional electronic data, such as banking records, general ledgers, sales and inventory data, etc.;
Querying and mining large data sets to discover transaction patterns, examining financial data and filtering for targeted information that utilize both traditional and predictive/advanced analytic methodologies; and,
Designing, developing and supporting data scientists by engineering the right data for data science/ machine learning.
All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law. PwC is proud to be an affirmative action and equal opportunity employer.
All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law.