Data Scientist II – Fraud Reporting

Truist

. Perform sophisticated data analytics using statistical and predictive analytics, machine learning modeling, classical econometrics, neural networks, and natural language processing .

Posted 10/14/2026full-timeCharlotte • North Carolina • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data analytics, statistical methods, and machine learning to drive actionable insights and improve business outcomes. Proficient in coding and deploying solutions in Python, SAS, and R while collaborating with cross-functional teams on data governance and analytics strategies.

Highest-signal resume keywords

Data AnalyticsMachine Learning ModelingStatistical MethodsPython ProgrammingSQL Data Extraction

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical AnalysisPredictive AnalyticsEconometricsNatural Language ProcessingData VisualizationData CleansingCalculusLinear AlgebraHadoopSpark

Soft Skills

CollaborationConsultationCommunicationProject Management

Tools & Technologies

SASRSQLJQueryNoSQLPigHive

Industry Keywords

Data ScienceData GovernanceRisk ManagementBusiness OutcomesStakeholder Engagement

Tech Stack

Tools & technologies

HadoopjQueryNoSQLPythonSparkSQL

About the role

Key responsibilities & impact

Perform sophisticated data analytics using statistical and predictive analytics, machine learning modeling, classical econometrics, neural networks, and natural language processing
Provide actionable insights that improve business outcomes and minimize risk
Consult with business leaders and stakeholders on leveraging analytics insights and building analytics strategies
Produce data visualizations to communicate insights and influence outcomes
Own 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
Write, document, and deploy custom code in Python, SAS, R, and other environments
Use, maintain, share, and collaborate through internal code repositories
Research and advocate adoption of emerging data science methods and technologies
Promote risk management throughout design, development, and deployment
Partner with cross-functional teams on data usage rules, data governance, and analytics capabilities

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, including 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
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, including SQL and JQuery
Working knowledge of Hadoop, Pig, Hive, NoSQL, and Spark
Experience managing multiple projects with tight deadlines in a collaborative environment
No employer sponsorship for work visa status or employment authorization, or immigration-related support
English language fluency required

Benefits

Comp & perks

Medical insurance
Dental insurance
Vision insurance
Life insurance
Disability insurance
Accidental death and dismemberment coverage
Tax-preferred savings accounts
401(k) plan
At least 10 days of vacation during the first year of employment
10 sick days
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)