8 days old

Data Scientist - Machine Learning Fraud Analytics - Senior Manager

PwC
New York, NY 10016
  • Jobs Rated
    7th

A career in our Forensic & Investigative Analytics practice, within Forensic Technology services, will provide you with the opportunity to help our clients protect their business in todays 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.


To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be an authentic and inclusive leader, at all grades/levels and in all lines of service. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.


As a Senior Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:

  • Take action to ensure everyone has a voice, inviting opinion from all.
  • Establish the root causes of issues and tackle them, rather than just the symptoms.
  • Initiate open and honest coaching conversations at all levels.
  • Move easily between big picture thinking and managing relevant detail.
  • Anticipate stakeholder needs, and develop and discuss potential solutions, even before the stakeholder realises they are required.
  • Develop specialised expertise in one or more areas.
  • Advise stakeholders on relevant technical issues for their business area.
  • Navigate the complexities of global teams and engagements.
  • Build trust with teams and stakeholders through open and honest conversation.
  • Uphold the firm's code of ethics and business conduct.

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.

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.

Categories

Jobs Rated Reports for Data Scientist

Posted: 2020-02-16 Expires: 2020-03-18

Before you go...

Our free job seeker tools include alerts for new jobs, saving your favorites, optimized job matching, and more! Just enter your email below.

Share this job:

Data Scientist - Machine Learning Fraud Analytics - Senior Manager

PwC
New York, NY 10016

Join us to start saving your Favorite Jobs!

Sign In Create Account
Data Scientist
7th2018 - Data Scientist
Overall Rating: 7/220
Median Salary: $111,840

Work Environment
Very Good
32/220
Stress
Very Low
41/220
Growth
Very Good
35/220
Powered ByCareerCast