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Internship Data Science R Jobs in Atlanta, GA (NOW HIRING)

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside ...

... R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine ... Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a ...

Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc...) * Strong knowledge of key programming concepts (e.g. split ...

Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc...) * Strong knowledge of key programming concepts (e.g. split ...

Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc...) * Strong knowledge of key programming concepts (e.g. split ...

... R, or SAS to prepare data for analysis, engineer features, visualize data, or support machine ... Bachelor's degree in Engineering, Mathematics, Statistics, Computer Science, Cybersecurity, or a ...

The role requires 6+ years of data science experience applied specifically to cybersecurity ... R , and SQL ; - Experience with machine learning frameworks ( TensorFlow , PyTorch ) and data ...

What You Will Bring: * 0-2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects.

What You Will Bring: * 0-2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects.

... interns on the team. · Other duties as assigned. Knowledge & Qualifications · Master of Science in a relevant field such as Computer Science, Statistics, Mathematics, Engineering, or Data Science ...

Data Scientist

Atlanta, GA · On-site +1

$95K - $110K/yr

What You Will Bring: * 0-2 years of experience in data science, analytics, machine learning, or a related field, including internships, research, senior projects, or meaningful independent projects.

... interns on the team. • Other duties as assigned. Knowledge & Qualifications • Master of Science in a relevant field such as Computer Science, Statistics, Mathematics, Engineering, or Data Science ...

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Internship Data Science R information

See Atlanta, GA salary details

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How much do internship data science r jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for internship data science r in Atlanta, GA is $21.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.63 and $23.56 per hour, depending on experience, location, and employer.

What types of projects can I expect to work on during a Data Science Internship at R?

As a Data Science intern at R, you will typically be involved in projects such as data cleaning, exploratory data analysis, and building predictive models under the guidance of experienced data scientists. You may also contribute to developing data visualizations and presenting insights to stakeholders. Interns often collaborate with cross-functional teams, including software engineers and business analysts, which provides valuable exposure to real-world data challenges and team-based problem solving.

What is the difference between Internship Data Science R vs Data Analyst Intern?

AspectInternship Data Science RData Analyst Intern
Required SkillsProficiency in R, statistical analysis, data visualizationExcel, SQL, basic statistical knowledge
Work EnvironmentData science teams, research projects, analytics departmentsBusiness units, marketing, finance, or operations teams
Industry UsageTech, finance, healthcare, research institutionsRetail, marketing, consulting, finance

Internship Data Science R focuses on applying R programming for statistical analysis and data modeling, often in research or technical environments. Data Analyst Internships emphasize data cleaning, visualization, and reporting using tools like Excel and SQL. Both roles require analytical skills but differ in technical depth and industry focus.

What is an Internship Data Science R?

An Internship Data Science R is a temporary position for students or recent graduates to gain practical experience in data science, with a focus on using the R programming language. Interns typically work under the guidance of experienced data scientists, assisting with data cleaning, analysis, visualization, and possibly building statistical models. This role helps interns develop technical and analytical skills, and provides exposure to real-world data-driven projects, often found in industries like finance, healthcare, or technology.

What are the key skills and qualifications needed to thrive as an Internship Data Science R, and why are they important?

To thrive as an Internship Data Science R, you need a solid grounding in statistics, data analysis, and programming with R, typically supported by coursework or a degree in a quantitative field. Familiarity with R packages (like tidyverse, ggplot2), data visualization tools, and version control systems such as Git is often required. Strong problem-solving skills, attention to detail, and effective communication help interns translate data insights into actionable recommendations. These abilities are crucial for supporting data-driven decision-making and contributing meaningfully to project teams in a professional environment.
Sr Data Scientist I (Actuarial Science)

Sr Data Scientist I (Actuarial Science)

LexisNexis

Alpharetta, GA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 16 days ago


LexisNexis rating

7.6

Company rating: 7.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

111th of 437 rated business services


Job description

Would you like to apply actuarial science and statistical modeling to build predictive models that directly influence underwriting, pricing, and risk decisions for insurers at scale?
About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within Insurance, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle - all while reducing risk. You can learn more about LexisNexis Risk at the link below.
https://risk.lexisnexis.com/insurance
About our Team
The Insurance Analytics team are the trusted leaders in analytics excellence, delivering innovative, data-driven solutions through cutting-edge data science and strategic risk solutions to drive market leadership, impactful change, and lasting value for our customers and stakeholders. The team is responsible for new product innovation, model development, and creating actionable insights for our customers. We work closely with the Vertical and Product teams to design and implement new solutions for the insurance and OEM markets. By harnessing the power of data, our analytics team empowers insurers to make informed decisions, optimize risk segmentation, and enhance underwriting strategies, ultimately driving success in an ever-evolving insurance landscape.
About the Role
Are you an actuarial professional who wants to build models that influence underwriting, risk segmentation, and decision-making across the insurance industry, without being confined to traditional rate-making roles?
We are seeking a Senior Data Scientist I with a strong actuarial foundation to join our Insurance Analytics team, focused on the commercial insurance market. In this role, you will design and develop predictive models that are embedded in carrier workflows and used to inform underwriting decisions, segmentation strategies, and downstream pricing models.
Unlike traditional actuarial roles, you will focus on building external-facing risk models and attributes that insurers integrate into their pricing and underwriting frameworks. This is an ideal opportunity for someone with actuarial training who enjoys applying statistical modeling and analytical thinking to broader insurance problems at scale.
Responsibilities:
  • Developing predictive risk models and attributes used by insurers in underwriting, segmentation, and decisioning workflows
  • Applying actuarial principles and statistical modeling techniques to assess risk and improve model performance
  • Designing and implementing models that are integrated into carrier underwriting processes and downstream pricing frameworks
  • Translating complex analytical outputs into clear, defensible insights for business and product stakeholders
  • Partner with Product and Vertical teams to solve insurance-specific problems related to risk evaluation and segmentation
  • Managing and analyzing large, complex datasets, including data storage, processing, and quality assurance.
  • Applying best practices for data validation, testing, and model performance monitoring.
  • Collaborating with team members to share knowledge, strengthen capabilities, and contribute to a strong analytical culture.
  • Maintaining a strong understanding of team tools, technologies, and evolving industry trends.
  • Communicating progress, insights, and outcomes clearly to stakeholders.
  • Supporting team excellence by upholding high standards of quality, accountability, and execution.

Requirements:
  • Minimum undergraduate degree in relevant field and 4+ years of relevant work experience
  • Or a master's degree in a relevant field and 2+ years of relevant work experience.
  • Or a PhD in a relevant field.
  • Strong actuarial foundation, including experience applying actuarial concepts to insurance risk, underwriting, or segmentation problems
  • Progress toward actuarial credentials (ASA or equivalent) strongly preferred
  • Strong expertise in Python. Coding skills in R, SQL, ECL are a plus.
  • Experience developing or supporting risk segmentation models (e.g., GLMs) in an insurance context and in Department of Insurance filings.
  • Experience translating actuarial models into production-ready analytical solutions.
  • Strong foundation in statistical and mathematical modeling, including model assumptions, diagnostics, and interpretability. This includes linear and non linear models along with ML techniques.
  • Extensive programming skills in Python and/or R for statistical modeling and data analysis
  • Strong ability as a self-starter to learn new technologies and to share cross-functional knowledge across the teams nice to have.

Technical/Professional Experience
  • Able to build or test new processes with senior guidance. Domain expert in Data Science, Actuarial Science and/or Statistical Analysis to build advanced models and roll into production.
  • Scopes and execute analytical approaches for moderately complex problems, seeking input where needed.
  • Supports, maintains, and enhances existing models (e.g., GLM and tree-based methods).
  • Applies statistical, mathematical, predictive modeling and analytical techniques to work with large, complex datasets from diverse sources.

Data Skills
  • Independently prepares, cleans, and transforms data for analysis and modeling.
  • Applies a range of data processing techniques and explores new methods to improve data quality and usability.

Project Management Skills
  • Owns and delivers components of projects independently, including planning and execution of key tasks.
  • Contributes to larger, more complex projects by executing defined workstreams and meeting timelines.

Domain/Industry Skills
  • Experience working with insurance data, risk modeling, or underwriting-related problems
  • Understanding of how predictive models are used within carrier underwriting and pricing workflows
  • Familiarity with regulatory or model governance considerations is a plus

Behavioral Competencies
  • Takes initiative and ownership of work, proactively addressing challenges and identifying opportunities for improvement.
  • Collaborates effectively with teammates, supporting a positive and accountable team environment.
  • Balances innovation with practical business needs and team priorities
  • Demonstrates accountability, follows through on commitments, and maintains high standards of work.
  • Shows willingness to stretch beyond core responsibilities and support team success.

Working for you:
We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
  • Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
  • Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
  • Wellbeing: Wellness platform with incentives, Employee Assistance and Time-off Programs
  • Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
  • Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
  • Health Savings, Health Care, Dependent Care and Commuter Spending Accounts

U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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