Data Scientist II -Card Fraud Analytics

Truist Bank•Atlanta, GA

9h•Onsite

About The Position

The position involves performing sophisticated analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk. It also requires providing consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics. Specifically, the role supports the fraud strategy function, developing and refining fraud rules, and identifying underperforming strategies. The teammate will independently perform sophisticated data analytics tailored to fraud problems, using various techniques like classical econometrics, machine learning, neural networks, and natural language processing on structured and unstructured data. The role involves communicating insights through compelling data visualizations, taking ownership of end-to-end data science solution design and technical delivery, and engaging with stakeholders to define business objectives and scope solution requirements.

Requirements

Bachelor’s degree and four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training
Exhibit understanding of statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests
Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components; working knowledge of calculus/differential equations, with understanding of stochastic processes
Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)
Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark
Experience in managing multiple projects with tight deadlines in a collaborative environment

Nice To Haves

Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering
Four years of relevant work experience if candidate lacks graduate degree
Previous experience in the banking or fin-tech industry
Experience with working with geo-location datasets used to identify patterns of fraud (online and/or offline)
Working knowledge and/or hands on fraud detection experience with card products, card processors, card networks, and one or more fraud rule systems such as Defense Edge, FDWC, Falcon Expert, Tsys Card Guard, Tsys Determinator, Broadcom 3DS, Token Administration, Visa Risk Manager

Responsibilities

Independently perform sophisticated data analytics (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data.
Produce compelling data visualizations to communicate insights and influence outcomes among a wide array of stakeholders.
Take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome.
Engage in stakeholder meetings to identify business objectives and scope solution requirements.
Independently write, document, and deploy custom code in a variety of environments (Python, SAS, R, etc.) to create predictive analytics applications.
Use, maintain, share and collaborate through Truist internal code repositories to foster continual learning and cross-pollination of skillsets.
Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist’s capabilities.
Exercise sound judgment and foster risk management culture throughout design, development, and deployment practices; partner with cross-functional teams to coordinate rules on data usage, data governance and analytics capabilities.
Support fraud strategy function, develop 3 or more fraud rules per month while conducting analyses to identify underperforming fraud strategies that need to be retired.
Participate at Card Fraud benchmarking forums with deep industry knowledge to help the team advance with modern fraud strategies.
Develop or leverage advanced analytics techniques of machine learning fraud rule generation to refit top 20% of fraud rules per fraud rule platform.

Benefits

medical
dental
vision
life insurance
disability
accidental death and dismemberment
tax-preferred savings accounts
401k plan
no less than 10 days of vacation (prorated based on date of hire and by full-time or part-time status) during their first year of employment
10 sick days (also prorated)
paid holidays
defined benefit pension plan (depending on the position and division)
restricted stock units (depending on the position and division)
deferred compensation plan (depending on the position and division)