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Data Science R Jobs in North Carolina (NOW HIRING)

Data Science Tutor

Greensboro, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Data Science Tutor

Charlotte, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Data Science Tutor

Durham, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Data Science Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Data Science Tutor

Matthews, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Data Science Tutor

Wilmington, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Data Science Tutor

Raleigh, NC · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... SQL, Python or R programming, hypothesis testing, and communication of data-driven insights.

Introduction to R/Python for Data Science, * Introduction to Data Visualization, * Data Communication, * Introduction to AI Ethics, * Data Science for Social Good, * Introduction to Data Science for ...

Introduction to R/Python for Data Science, * Introduction to Data Visualization, * Data Communication, * Introduction to AI Ethics, * Data Science for Social Good, * Introduction to Data Science for ...

Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages. Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ...

Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages. Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ...

Director of Data Science

Charlotte, NC · On-site +1

$153K - $229K/yr

Dir Data Science - GD06AE We're determined to make a difference and are proud to be an insurance ... and/or R. Prior Management Experience Expertise in the end-to-end modeling lifecycle, from ...

Develop predictive models and statistical analyses using Python R or similar tools * Deploy monitor ... Work with stakeholders to translate business objectives into data science solutions and actionable ...

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Showing results 1-20

Data Science R information

See North Carolina salary details

$34.1K

$111.5K

$178.6K

How much do data science r jobs pay per year?

As of Jul 15, 2026, the average yearly pay for data science r in North Carolina is $111,545.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,500.00 and $123,600.00 per year, depending on experience, location, and employer.

What is a Data Science R job?

A Data Science R job involves using the R programming language for data analysis, statistical modeling, and machine learning. Professionals in this role work with large datasets, clean and preprocess data, apply predictive modeling techniques, and visualize insights. They often use libraries like ggplot2, dplyr, and caret to manipulate data and build models. This role is common in industries such as finance, healthcare, and marketing, where data-driven decision-making is essential. Strong statistical knowledge, programming skills, and domain expertise are key to success in this position.

What are the typical daily tasks for a Data Science R professional in most organizations?

In most organizations, Data Science R professionals spend their days gathering and cleaning data, performing exploratory data analysis with R, building and evaluating predictive models, and generating data visualizations to communicate results. They often meet with cross-functional teams to understand business needs, translate them into data projects, and present key findings. Additionally, they may write reproducible R scripts, maintain data pipelines, and document their methodologies. Collaboration, experimentation, and clear communication are integral parts of the role, enabling solutions that directly impact business outcomes.

What are the key skills and qualifications needed to thrive in the Data Science R position, and why are they important?

To thrive as a Data Science R professional, you need solid expertise in statistics, machine learning, and programming in R, often supported by a degree in data science, statistics, or a related field. Experience with R-based data analysis libraries, visualization tools like ggplot2, and familiarity with databases or cloud platforms is typically expected; certifications in data science or R programming can be advantageous. Strong problem-solving abilities, attention to detail, and effective communication with stakeholders help distinguish top performers in this role. These skills are essential for delivering actionable insights from complex datasets and driving data-informed decision-making within organizations.

What are the most commonly searched types of Data Science R jobs in North Carolina? The most popular types of Data Science R jobs in North Carolina are:
Infographic showing various Data Science R job openings in North Carolina as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $111,545 per year, or $53.6 per hour.
Director, Data Science

Director, Data Science

Fidelity Investments

Durham, NC • On-site

Full-time

Retirement

Re-posted 5 days ago


Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 266 frontline employees who took The Breakroom Quiz

17th of 148 rated financial services


Job description


Position Description:
Leads and oversees end-to-end data science initiatives, guiding teams through data cleansing, preparation, annotation, feature engineering, exploratory analysis, and model development. Provides strategic direction on Machine Learning (ML) pipeline architecture, ensures alignment with business objectives, and drives cross-functional collaboration to deliver scalable, high-impact solutions. Draws on in-depth knowledge of the business or function to provide business unit-wide solutions by building, testing and monitoring AI models. Researches and recommends new technologies, and seizes opportunities by staying abreast of publications, tools, and techniques from the global Artificial Intelligence (AI/ML) community, in support of the strategic direction of the business unit and to achieve business-unit-wide solutions.
Primary Responsibilities:
  • Identifies business opportunities and evaluates best approaches for predictive or prescriptive analytics.
  • Implements best practices for model development, iteration, as well as code management and conducts code reviews.
  • Draws key business insights from advanced quantitative analyses and presents findings to broader audience.
  • Leads the design and deployment of advanced analytics solutions that convert raw data into actionable intelligence.
  • Delivers scalable insights, while aligning analytics infrastructure with business priorities.
  • Directs the development and integration of analytics frameworks that transform raw data into strategic insights.
  • Ensures solutions are scalable, business-aligned, and drive data-informed decision-making across the organization.
  • Leads and oversees the full AI/ML lifecycle -- data ingestion, model development, training, deployment, and monitoring.
  • Identifies and consults with internal and external technical resources to produce cross-company strategic designs.
  • Consults on deployment of major project deliverables.
  • Initiates and drives project or strategy discussions with users or external groups to resolve issues.
  • Sets vision, goals, and direction of team/organization.
  • Plans and leads organization-wide initiatives.
  • Provides leadership, technical supervision, and expertise to multiple teams in broad technical areas on complex organization-wide projects.
  • Advises senior management on technical strategy.
  • Regularly provides guidance, training, and coaching to other team members for performance and career development.
  • Identifies and plans for future resource needs.

Education and Experience:
Bachelor's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and six (6) years of experience as a Director, Data Science (or closely related occupation) designing and building complex and scalable Artificial Intelligence (AI) pipelines to improve customer experience and drive business results in the financial services industry.
Or, alternatively, Master's degree in Analytics, Computer Science, Data Science, Operations Research, Economics, or a closely related field (or foreign education equivalent) and four (4) years of experience as a Director, Data Science (or closely related occupation) designing and building complex and scalable Artificial Intelligence (AI) pipelines to improve customer experience and drive business results in the financial services industry.
Skills and Knowledge:
Candidate must also possess:
  • Demonstrated Expertise ("DE") developing supervised and unsupervised Machine Learning (ML) algorithms -- regression, gradient boosting trees/random forest, neural network, feature selection/reduction, clustering, and parameter tuning -- using R, Python, and SAS programming languages; and analyzing and evaluating model results by creating data visualizations and business intelligence reports in Tableau and Adobe Analytics.

  • DE performing data wrangling and feature engineering for large, complex data across Cloud and on-premise data warehouses -- Oracle, Greenplum/Postgres, Hadoop/Hive, Snowflake, S3, and Redis -- using SQL, Python, and database specific SQL; standardizing and optimizing complex queries using database techniques -- partitioning and parallel processing; aggregating time series and transaction tables; creating appropriate features for modeling out of structured and unstructured data; detecting and preventing data leakage and model biases through model fairness measures using open-source AI fairness and ethics libraries.

  • DE analyzing technology solutions for supporting model deployment and integration in Cloud and on premise environments; and building model deployment and integration workflows on Amazon Web Services (AWS), on-premise Hadoop, and UNIX platforms through Git, Jenkins, Python scripts, cron jobs, step functions, Docker images, and APIs.

  • DE migrating existing AI/ML processes from on-premise environments to AWS platforms, using Extract- Transform-Load (ETL) procedures, Python, and Docker containers; creating data quality guardrails to validate model inputs and outputs using ICEDQ; and addressing financial services Cloud security constraints and record systems for workplace services -- 401(K), defined benefits, and workplace compensation and retirement plans, using AWS security tools.

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Certifications:
Category:
Data Analytics and Insights
Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

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