The Client Protection Organization is looking for an experienced data scientist to join our team as a Fraud Data Scientist. In this role, you will be expected to work with our lead data scientist and the team executive as well as our internal analytics, technology, product and policy partners to deploy advanced analytical solutions with the goal of reducing fraud losses, reducing false positive declines at the point-of-sale, improving client experience, and ensuring the Bank minimizes its total cost of fraud. Some tasks that this role may be responsible for include (but are not limited to):
* Model development (neural network, deep learning, random forest) * Link analysis to find deeply-connected first- and third-party fraud networks * Text mining/sentiment analysis/natural language processing * Unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies
In addition, the role will be expected to work with the lead data scientist and stakeholders to help develop the data strategy for client protection to ensure the organization has the proper data to make the right decisions, with a priority on data availability in real-time, and generating true customer-level views able to make intelligent fraud decisions leveraging the entirety of our interactions with a customer.
* Bachelors degree in a quantitative discipline such as mathematics, engineering, economics, finance, business, computer science. Masters degree or higher preferred. In lieu of a specific degree, advanced certifications in combination with strong experience will also be considered. * The candidate must be at an advanced to expert level with Python, with proficient-or-better skills expected in SAS and SQL * Must have 1+ years experience with data science, with preference working in financial services. Strong preference to experience in fraud or cybersecurity * Candidate must have a proven track record of building and deploying analytical solutions that have resulted in material financial results and extensive management experience. Ability to work in a fast-paced, dynamic environment is critical. Must have exceptional organizational, project management and communications skills.
* Solid knowledge of R, Java or Spark, and various commercial and model generation software * Should additionally have familiarity with other tools such as HUE, Hive, and other data gathering tools.Also, NLP and Image Recognition a plus.
Responsible for developing quantitative/analytic models and applications in support of the firm's risk management effort. This role focuses on the development of operations/data management policies, strategies and operational guidelines for the organization's various financial products as they relate to the analysis, tracking, and reporting of various risk metrics. This role often possesses an advanced degree in physics, applied mathematics, statistics/probability or another heavy quantitative discipline. Quantitative analytic staff is focused on and responsible for the development of the theory and mathematics behind various models. Individual Contributor and reports to Quant Operations Manager
Posting Date: 05/03/2019
Location: Newark, DE, Deerfield I, 655 Paper Mill Rd, Jacksonville, FL, BANK OF AMERICA OFFICE PARK, 9000 SOUTHSIDE BLVD, Chicago, IL, LAKE / N LASALLE BC, 203 N La Salle St, New York, NY, 50 Rockefeller Plaza (NY1050), - United States
Travel: Yes, 10% of the time
Full / Part-time: Full time
Hours Per Week: 40
Shift: 1st shift
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