Fraud Data Scientist II Job at Truist Inc, Atlanta, GA

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  • Truist Inc
  • Atlanta, GA

Job Description

The position is described below. If you want to apply, click the Apply Now button at the top or bottom of this page. After you click Apply Now and complete your application, you'll be invited to create a profile, which will let you see your application status and any communications. If you already have a profile with us, you can log in to check status.

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If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (careers@truist.com?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 analytics (statistical and predictive analytics, machine learning modeling, etc.) to provide actionable insights that improve business outcomes and minimize risk. Provide consultation to business leaders and other stakeholders on how to leverage analytics insights and build strategies around analytics. Lead small projects with manageable risks and resource requirements; play significant roles in larger, more complex initiatives. Act as a resource for teammates with less experience.

For this opportunity, Truist will not sponsor an applicant for work visa status or employment authorization, nor will we offer any immigration-related support for this position (including, but not limited to H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN-1 or TN-2, E-3, O-1, or future sponsorship for U.S. lawful permanent residence status.)

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.

  1. Perform sophisticated data analytics (encompassing data mining, inferential statistical analysis, and predictive analytics, for example) on structured and unstructured data. Identify actionable insights from various (or multiple) sources of data that measurably improve business outcomes or reduce business risk.

  2. Support new, ongoing, and strategic projects and take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome.

  3. Extract and evaluate information gathered from multiple sources, resolve data conflicts and customize communication of key data findings, while providing recommendations to diverse audiences.

  4. Provide analytical consulting and thought leadership to various business areas and fosters strategic and positive relationship with business partners.

  5. Co-design the optimal solutions to solve the complex business problems with advanced data science capabilities to create business value. Emphasize reusability and scalability in all design, development, deployment and mentoring activities through implementing consistent coding standards and best practices, focusing on clarity of communication across stakeholder groups and maintaining rigorous documentation.

  6. 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; help with the overall risk management for the team.

  7. Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist's 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.

  1. Bachelor's degree in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training

  2. Minimum of six years of related experience

  3. Demonstrate domain expertise (SME) in one or more areas relevant to banking, financial services, fin-tech, quantitative risk management, and/or financial regulation; this will be demonstrated by several years of career progression in roles of increasing responsibility

  4. In-depth knowledge in practices, theories and methodologies associated with the professional discipline such as statistics, programming (such as Python, R, SAS, etc.), machine learning, model development, business information visualization, etc.

  5. Ability to maintain a high level of competency in statistical and analytical principles, tools, and techniques

  6. Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark

  7. Experience in managing multiple projects with tight deadlines in a collaborative environment

Preferred Qualifications:

  1. Master's degree or PhD in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering

  2. Ten years of relevant work experience if candidate lacks graduate degree

  3. Previous experience in the banking or fin-tech industry

  4. Experience working with data science workspace within Adobe Enterprise Platform

  5. Experience working with Graph Databases, graph query language, and related algorithms

Additional Job Description:

  • Experience analyzing fraud trends using large datasets , applying statistical techniques, SQL, and/or data-science tools to identify anomalies, build rules, or evaluate model performance.

  • Working experience with real-time fraud decisioning platforms , such as Falcon, Actimize, SAS Fraud Management, or similar machine-learning-driven systems.

  • Hands-on expertise with fraud detection tools and data signals , including device intelligence, behavioral biometrics, consortium data, third-party risk scoring, and velocity or link-analysis tools.

  • Proven ability to translate fraud risk requirements into actionable rules, model features, detection logic, or platform configurations.

  • Strong understanding of payment ecosystems , including card network rules, issuer/acquirer authorization flows, chargeback lifecycle, and dispute management.

  • Background in fraud strategy design , including rule optimization, model monitoring, and roadmap planning.

  • Experience working with cross-functional teams (Product, Engineering, Compliance, Operations) to implement fraud-risk initiatives.

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 is an Equal Opportunity Employer that does not discriminate 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.

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Job Tags

Permanent employment, Full time, Work experience placement, H1b, Work visa, Shift work, Day shift

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