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Data Science Research Intern Jobs in Raleigh, NC

SmartIMS Inc.

Sr.Data Scientist II

Raleigh, NC · On-site

Mentor team members and provide technical leadership in data science and AI. Required ... Familiarity with legal text corpora, citation networks, or legal research workflows. * Experience ...

NextDeavor Inc.

Embedded Data Scientist

Morrisville, NC · On-site

$130K - $150K/yr

You will work closely with researchers and engineering teams to compress, characterize, and deploy ... Bachelor's degree in Mathematics, Data Science, Computer Science, Computer Engineering, or a ...

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Data Science Research Intern information

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$11

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How much do data science research intern jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for data science research intern in Raleigh, NC is $21.88, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $23.85 per hour, depending on experience, location, and employer.

What does a data science research intern do?

A Data Science Research Intern works on analyzing data, building predictive models, and supporting research projects under the guidance of experienced data scientists. Their tasks often include cleaning and visualizing data, implementing machine learning algorithms, and evaluating model performance. Interns may also help with literature reviews, prototyping new solutions, and presenting findings to the team. This role provides hands-on experience with real-world datasets and the opportunity to learn industry-standard tools and techniques.

What skills and qualifications are needed to thrive as a data science research intern?

To thrive as a Data Science Research Intern, you need a solid grounding in statistics, programming (typically Python or R), and data analysis, usually backed by coursework or a degree in a quantitative field. Familiarity with tools like Jupyter Notebooks, machine learning libraries (e.g., scikit-learn, TensorFlow), and version control systems (e.g., Git) is commonly expected. Strong problem-solving abilities, curiosity, and effective communication make candidates stand out by enabling them to tackle complex problems and share insights clearly. These skills are essential for contributing meaningful research, collaborating with team members, and translating data findings into actionable results.

How do data science research interns typically collaborate with full-time data scientists and engineering teams?

Data Science Research Interns often work closely with full-time data scientists to support ongoing projects, contribute to research discussions, and assist in developing analytical models. They may also interact with engineering teams to understand data pipelines, verify data integrity, and help implement prototypes into production environments. Regular meetings, code reviews, and paired problem-solving sessions are common, providing interns with valuable mentorship and exposure to real-world workflows. This collaborative environment helps interns build both technical and communication skills while making meaningful contributions to the team's goals.

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Data Science Research Intern jobs near you
Infographic showing various Data Science Research Intern job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $45,502 per year, or $21.9 per hour.

Senior Data Scientist[Remote]- W2 Role

SmartIPlace

Raleigh, NC • On-site

Contractor

Posted 15 days ago

Job description

Senior Data Scientist II
Position: Senior Data Scientist II
Location: Remote (EST) — Hybrid in Raleigh, NC preferred
Rate Type: BH W2
Duration: 6 months, with possible extension/conversion
Interview Process: 2 rounds via video

Position Overview

LexisNexis is seeking experienced Senior Data Scientist II professionals to develop innovative, customer-facing data science and AI solutions. The ideal candidate will have strong expertise in modern data science, Generative AI, LLMs, RAG, agentic AI, unstructured data, and production machine learning.

You will work closely with Machine Learning Engineers (MLEs) and cross-functional teams throughout the product development and production lifecycle, turning complex data into scalable, customer-focused solutions.

Required Qualifications

  • 8+ years of total professional experience in data science, machine learning, or a closely related field.
  • 5+ years of recent Data Science experience, with hands-on expertise in areas such as:
    • MCP
    • RAG implementations, evaluations, validations, and proof-of-concepts
    • Agentic AI
    • Generative AI
    • LLM applications
    • Unstructured data
  • Proven experience building customer-facing data science or AI products.
  • Experience partnering with Machine Learning Engineers (MLEs) throughout the production lifecycle.
  • Strong Python programming skills.
  • Strong understanding of machine learning algorithms, including:
    • Deep Learning
    • Gradient Boosting
    • Random Forests
  • Experience working directly with Large Language Models (LLMs) and Transformer-based architectures, including:
    • BERT
    • RoBERTa
    • T5
  • Hands-on experience applying LLM technologies such as:
    • ChatGPT
    • GPT-3.5
    • Claude
    • Mistral
  • Experience working with large datasets and distributed computing systems, such as Hadoop and Spark.

Preferred Qualifications

  • Experience working within large enterprise environments.
  • Experience taking AI/ML solutions from experimentation and proof-of-concept through production.
  • Strong understanding of modern Generative AI and LLM ecosystem.
  • Experience working with cross-functional teams to deliver business and customer-focused solutions.

Key Responsibilities

  • Develop advanced data science and AI solutions using complex datasets.
  • Design, implement, evaluate, and validate RAG, agentic AI, MCP, and Generative AI solutions.
  • Work with unstructured data to extract meaningful insights and develop innovative AI applications.
  • Apply machine learning and deep learning techniques to solve complex business problems.
  • Work directly with LLMs and Transformer-based architectures.
  • Collaborate closely with MLEs to move models and AI solutions into production.
  • Contribute to the full product lifecycle, from research and experimentation through deployment and optimization.
  • Analyze large-scale datasets using distributed computing technologies such as Spark and Hadoop.
  • Partner with cross-functional teams to translate business requirements into data-driven solutions.
  • Drive actionable insights that support business strategy, customer experience, and product growth.
  • Stay current with emerging developments in Generative AI, LLMs, machine learning, and AI engineering.

Ideal Candidate

The ideal candidate is a senior-level Data Scientist with strong hands-on Generative AI/LLM experience, particularly someone who has recently worked on RAG, MCP, agentic AI, unstructured data, and customer-facing AI products and has experience taking solutions into production.

Must-Have Keywords:
Python | Data Science | Generative AI | LLM | RAG | MCP | Agentic AI | Unstructured Data | Machine Learning | Deep Learning | Transformers | BERT | RoBERTa | T5 | Spark | Hadoop | Customer-Facing Products | MLE Collaboration

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

Social media

Facebook

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