Data Scientist 2-3 - Card Fraud Analytics

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Send an email to Accessibility (?subject=Accommodation%20request) (accommodation requests only; other inquiries won't receive a response). Regular or Temporary: Regular Language Fluency: English (Required) Work Shift: 1st shift (United States of America) Please review the following job description: Perform sophisticated card fraud analyses and strategy support using advanced analytics & data science tools to provide actionable insights and real-time changes to card fraud detection tools that improve business outcomes and minimize fraud risk.

A key part of the role will be regularly providing active and guiding consultation to business leaders and other stakeholders on best methods of leveraging analytics and fraud strategies to reduce gross fraud while maintaining a world class customer experience for active card purchasing customers using our credit and debit card payment products at Truist Bank.

This role will actively support multiple real-time fraud detection rule systems where the role will be actively be involved with building, developing, and demonstrating a mastery of card, fraud, and advanced analytics combined skill sets in an area with an abundance of vast/rich data features to work with.

ESSENTIAL DUTIES AND RESPONSIBILITIES Following is a summary of the essential functions for this job.

Other duties may be performed, both major and minor, which are not mentioned below.

Specific activities may change from time to time.

Perform sophisticated card fraud analyses and strategy support using advanced analytics & data science tools to provide actionable insights and real-time changes to card fraud detection tools that improve business outcomes and minimize fraud risk.

A key part of the role will be regularly providing active and guiding consultation to business leaders and other stakeholders on best methods of leveraging analytics and fraud strategies to reduce gross fraud while maintaining a world class customer experience for active card purchasing customers using our credit and debit card payment products at Truist Bank.

This role will actively support multiple real-time fraud detection rule systems where the role will actively be involved with building, developing, and demonstrating a mastery of card, fraud, and advanced analytics combined skill sets in an area with an abundance of vast/rich data features to work with.

Entry-level responsibilities Supports fraud strategy function, develops 3 or more fraud rules per month while conducting analyses to identify underperforming fraud strategies that need to be retired.

In supporting rule analysis, Teammate should be able to Independently perform sophisticated data analytics that fit to the fraud problem being observed (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 outcomes.

Engage in stakeholder meetings to identify business objectives and scope solution requirements With minimal guidance, 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 fosters 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.

QUALIFICATIONS Required Qualifications: The requirements listed below are representative of the knowledge, skill and/or ability required.

Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

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 Preferred Qualifications: 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 Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompensations, principal components, working knowledge of calculus/differential equations, with understand of stochastic processes.

Participant at Card Fraud benchmarking forums with deep industry knowledge to help our team advance with modern fraud strategies.

Capability to develop or leverage the advanced analytics techniques of machine learning fraud rule generation to refit our top 20% of fraud rules per fraud rule platform Experience with working with geo-location data-sets 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 OTHER JOB REQUIREMENTS / WORKING CONDITIONS Sitting Constantly (More than 50% of the time) Visual / Audio / Speaking Able to access and interpret client information received from the computer and able to hear and speak with individuals in person and on the phone.

Manual Dexterity / Keyboarding Able to work standard office equipment, including PC keyboard and mouse, copy/fax machines, and printers.

Availability Able to work all hours scheduled, including overtime as directed by manager/supervisor and required by business need.

Travel Minimal and up to 10% General Description of Available Benefits for Eligible Employees of Truist Financial Corporation: All regular teammates (not temporary or contingent workers) working 20 hours or more per week are eligible for benefits, though eligibility for specific benefits may be determined by the division of Truist offering the position.

Truist offers medical, dental, vision, life insurance, disability, accidental death and dismemberment, tax-preferred savings accounts, and a 401k plan to teammates.

Teammates also receive 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, along with 10 sick days (also prorated), and paid holidays.

For more details on Truist’s generous benefit plans, please visit our Benefits site ( . Depending on the position and division, this job may also be eligible for Truist’s defined benefit pension plan, restricted stock units, and/or a deferred compensation plan.

As you advance through the hiring process, you will also learn more about the specific benefits available for any non-temporary position for which you apply, based on full-time or part-time status, position, and division of work.

Truist supports a diverse workforce and is an Equal Opportunity Employer that does not discriminate against individuals on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status or other classification protected by law.

Truist is a Drug Free Workplace.

EEO is the Law ( Pay Transparency Nondiscrimination Provision ( E-Verify (