Data Scientist I

Jobtailor; Raleigh (NC); On-site; USD 95,000 - 120,000; Full time

Job summary

Truist is seeking a data scientist to perform advanced statistical and predictive analytics, building machine learning models and data visualizations that drive actionable business outcomes.

You will collaborate with business leaders to translate objectives into analytics solutions, work with structured and unstructured data using Python, SAS, and R, andown end-to-end delivery while adhering to risk management and governance standards.

Qualifications

• Bachelor's degree plus 0–4+ years in a quantitative field.
• Strong knowledge of statistics, probability, econometrics, time-series.
• Familiarity with linear algebra for optimization.
• Calculus/differential equations with understanding of stochastic processes.
• Data cleansing and preparation methodologies including regex and outlier treatment.
• Strong SQL/data extraction skills.
• Experience with Hadoop, Pig, Hive, NoSQL, Spark.
• Experience managing multiple projects with tight deadlines.
• Willingness to work overtime; up to 10% travel.
• English fluency.
• Master’s or PhD preferred; 4 years if no graduate degree.
• Previous banking/fintech experience preferred.

Responsibilities

• Perform statistical and predictive analytics and ML modeling to generate actionable insights.
• Consult with business leaders on analytics strategy and leveraging insights.
• Independently perform data analytics using econometrics, ML, neural nets, NLP on structured/unstructured data.
• Produce data visualizations to communicate insights and influence outcomes.
• Own end-to-end data science solution design, technical delivery, and measurable business outcomes.
• Engage stakeholders to identify objectives and scope solution requirements.
• Write, document, and deploy Python, SAS, R code for predictive analytics apps.
• Use and share code via Truist internal repositories.
• Research emerging data science methods and technologies.
• Apply risk management and governance for data usage and analytics capabilities.

Skills

Statistical Methods

Machine Learning

Data Visualization

Python Programming

SQL Data Extraction

Education

Bachelor's degree

Master’s degree or PhD (preferred)

Tools

Python

SAS

R

SQL

Hadoop

Pig

Hive

NoSQL

Spark

JQuery

Job description

• Perform sophisticated statistical and predictive analytics and machine learning modeling to provide actionable insights
• Provide consultation to business leaders and stakeholders on leveraging analytics insights and developing analytics strategies
• Independently perform data analytics using econometrics, machine learning, neural networks, and natural language processing on structured and unstructured data
• Produce data visualizations to communicate insights and influence 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 risk management practices and collaborate on data usage, governance, and analytics capabilities

Requirements

• Bachelor’s degree and zero to 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 environments such as SQL and JQuery
• Working knowledge of Hadoop, Pig, Hive, NoSQL, and/or Spark
• Experience managing multiple projects with tight deadlines in a collaborative environment
• Ability to work all scheduled hours, including overtime as directed
• Minimal travel, up to 10%
• English language fluency required
• Master’s degree or PhD in a quantitative field (preferred)
• Four years of relevant work experience if lacking a graduate degree (preferred)
• Previous banking or fintech industry experience (preferred)

Core Competencies

Demonstrates expertise in statistical and predictive analytics, machine learning, and data visualization to drive actionable insights and business outcomes. Proficient in coding with Python, SAS, and R, while applying risk management practices and collaborating on data governance.

Highest-signal resume keywords

• Statistical Methods
• Machine Learning Modeling
• Data Visualization
• Python Programming
• SQL Data Extraction

Hard Skills

• Statistical Methods
• Predictive Analytics
• Machine Learning
• Econometrics
• Data Cleansing
• Data Preparation
• Linear Algebra
• Calculus
• Time-Series Analysis
• Natural Language Processing

Soft Skills

• Collaboration
• Consultation
• Project Management
• Stakeholder Engagement
• Communication

Industry Keywords

• Data Science
• Banking
• Fintech
• Quantitative Analysis
• Risk Management

Tools & Technologies

• Python
• SAS
• R
• SQL
• Hadoop
• Pig
• Hive
• NoSQL
• Spark
• JQuery