Data Scientist II – Fraud Reporting

Truist

Data Scientist II applying machine learning, econometrics, and predictive analytics to fraud reporting at Truist, a financial services company. Delivering visualizations, custom analytics applications, and risk-focused insights for business stakeholders.

Posted 8/5/2026full-timeCharlotte • North Carolina • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data analytics, including classical econometrics, machine learning, and natural language processing, while effectively communicating insights through data visualizations. Proficient in Python, SAS, R, and SQL, with a strong understanding of statistical methods and data governance.

Highest-signal resume keywords

Data AnalyticsMachine LearningPython ProgrammingStatistical MethodsData Visualization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

EconometricsNatural Language ProcessingPredictive AnalyticsData CleansingStatistical TestsLinear AlgebraCalculusSQLHadoopData Governance

Soft Skills

Stakeholder EngagementCollaborationProject ManagementCommunication

Tools & Technologies

SASRTruist Code RepositoriesJQueryNoSQLSpark

Industry Keywords

BankingFintechQuantitative Analysis

Tech Stack

Tools & technologies

HadoopjQueryNoSQLPythonSparkSQL

About the role

Key responsibilities & impact

Independently perform sophisticated data analytics using classical econometrics, machine learning, neural networks, and natural language processing on structured and unstructured data
Produce compelling data visualizations to communicate insights and influence stakeholder outcomes
Own end-to-end data science solution design, technical delivery, and measurable business outcomes
Engage stakeholders to identify business objectives and scope solution requirements
Write, document, and deploy custom code in Python, SAS, R, and other environments to create predictive analytics applications
Use, maintain, share, and collaborate through Truist internal code repositories
Research and advocate adoption of emerging data science methods and technologies
Apply sound judgment and promote risk management throughout design, development, and deployment
Partner with cross-functional teams on data usage rules, data governance, and analytics capabilities
Provide actionable insights to improve business outcomes and minimize risk
Consult with business leaders and stakeholders on leveraging analytics insights and developing analytics strategies

Requirements

What you’ll need

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
Understanding of statistical methods, classical statistics, probability theory, econometrics, time-series, and primary statistical tests
Familiarity with linear algebra for optimization, complex matrix operations, eigenvalue decompositions, and principal components
Working knowledge of calculus/differential equations and understanding of stochastic processes
Understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment
Strong familiarity with data extraction in SQL, JQuery, and other environments
Working knowledge of Hadoop, Pig, Hive, NoSQL, and/or Spark
Experience managing multiple projects with tight deadlines in a collaborative environment
English language fluency required
Preferred: Master's degree or PhD in a quantitative field
Preferred: Previous banking or fintech industry experience
Truist will not sponsor work visas, employment authorization, or immigration-related support for this position

Benefits

Comp & perks

Medical insurance
Dental insurance
Vision insurance
Life insurance
Disability insurance
Accidental death and dismemberment coverage
Tax-preferred savings accounts
401k plan
At least 10 days of vacation during the first year of employment, prorated
10 sick days, prorated
Paid holidays
Defined benefit pension plan, depending on position and division
Restricted stock units, depending on position and division
Deferred compensation plan, depending on position and division