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Internship Machine Learning Quant Jobs in Durham, NC

Analogdevices

Mixed Signal Engineer Intern

Durham, NC

$22 - $41/hr

Develop and validate machine learning models for analog design automation. * Analyze design data ... Internship/Cooperative Required Travel: Yes, 10% of the time The expected wage range for a new hire ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

... quantitative discipline. * Experience in computational image analysis, digital pathology, machine learning, or biomedical data science. * Strong programming and software development skills.

Duke University

Postdoctoral Associate

Durham, NC · On-site

... quantitative discipline. * Experience in computational image analysis, digital pathology, machine learning, or biomedical data science. * Strong programming and software development skills.

Duke University

Postdoctoral Associate

Durham, NC · On-site

Familiarity with causal inference methods or machine learning approaches * Demonstrated experience ... Position Description: Quantitative & Computational Analysis: The Postdoctoral Associate will ...

Duke University

Postdoctoral Associate

Durham, NC · On-site

Familiarity with causal inference methods or machine learning approaches * Demonstrated experience ... Position Description: Quantitative & Computational Analysis: The Postdoctoral Associate will ...

CIMA

Psychometrician

Durham, NC · Remote

$80K - $95K/yr

You Have: * Ph.D. in Psychometrics, I/O psychology, Quantitative Psychology, Educational ... Experience with statistical/psychometric programming, machine learning, Natural Language Processing ...

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Internship Machine Learning Quant information

See Durham, NC salary details

$24.6K

$41.1K

$85K

How much do internship machine learning quant jobs pay per year?

As of Sep 4, 2026, the average yearly pay for internship machine learning quant in Durham, NC is $41,149.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,400.00 and $44,400.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

What are the most commonly searched types of Machine Learning Quant jobs in Durham, NC?

The most popular types of Machine Learning Quant jobs in Durham, NC are:

What are popular job titles related to Internship Machine Learning Quant jobs in Durham, NC?

For Internship Machine Learning Quant jobs in Durham, NC, the most frequently searched job titles are:

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The top searched job categories for Internship Machine Learning Quant jobs in Durham, NC are:

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Cities near Durham, NC with the most Internship Machine Learning Quant job openings:

Internship Machine Learning Quant jobs near you

Principal Statistical Methodologist, Raleigh, NC

UCB

Raleigh, NC • On-site

Full-time

Re-posted 13 days ago

Key responsibilities

  • Develop and apply advanced computational and statistical methods, including machine learning, AI, and scenario evaluation, to inform design, analysis, and decision-making across development.

  • Build robust, well-engineered, reusable tools and workflows that bring these methods into routine use, ensuring reproducibility and software quality.

  • Partner with statisticians and cross-functional colleagues to identify where computational and data-driven methods add the most leverage and translate complex approaches into clear insight for technical and non-technical audiences.

Job description

Make your mark for patients
We are looking for a Principal Statistical Methodologist who is curious, collaborative, and strategic to join our Statistical Innovation team within Biometric and Data Sciences (BDS), based in our Raleigh, NC (US) offices.
About the role
As a Principal Statistical Methodologist, you will help shape how evidence is generated, modeled, and communicated across the drug development lifecycle, bringing modern computational and machine-learning methods to bear on real R&D decisions. You will develop and apply advanced data-driven and model-based approaches-drawing on statistics, machine learning, and AI-translate them into robust, reusable tools, and partner across functions to put them to work where they impact drug development decision-making. You will also contribute to the group's scientific profile through publications and external collaboration.
Who you will work with
You will be working in a team that provides statistical consultancy across therapy areas and development stages, partnering closely with colleagues in clinical development, regulatory strategy, data science, and medical affairs. The team values curiosity and problem-solving, practical innovation, clear communication, and collaboration, bringing novel quantitative and computational approaches into real study decisions and sharing learnings with the wider scientific community.
What you will do
  • Develop and apply advanced computational and statistical methods, including machine learning, AI, and scenario evaluation using modern simulation approaches, to inform design, analysis, and decision-making across development.
  • Build robust, well-engineered, reusable tools and workflows that bring these methods into routine use, with attention to reproducibility and software quality.
  • Bring a quantitative lens with appropriate rigor to emerging problems such as synthetic and external control data, causal inference, and digital-twin or simulation-based approaches.
  • Partner with statisticians and cross-functional colleagues to identify where computational and data-driven methods add the most leverage and translate complex approaches into clear insight for technical and non-technical audiences.
  • Contribute to internal capability building by sharing tools, code, and methods across the team and wider organization.
  • Contribute to the group's external profile through scientific publications, conference presentations, and participation in cross-industry initiatives and working groups.

Interested? For this role we're looking for the following education, experience and skills Minimum qualifications
  • Doctoral degree in statistics, biostatistics, mathematics, computer science with a strong quantitative/statistical component, or a closely related discipline with a solid grounding in statistical inference and uncertainty.
  • Minimum of 3 years of experience within the pharmaceutical industry.

Preferred qualifications
  • Experience in advanced computational methodology for clinical development (early to late stage) is an advantage. Direct entry may be considered.
  • Strong, multi-language scientific programming skills (R and Python preferred; software-engineering practices such as version control, testing, and reproducible workflows a clear advantage).
  • Demonstrated expertise in machine learning and/or AI methods, with hands-on experience applying them to real problems; experience with large language models, causal inference, synthetic data, or digital twin/simulation approaches is a strong advantage.
  • Sound knowledge of ICH guidelines and understanding of regulatory requirements from major health authorities.
  • Ability to work effectively with autonomy, manage multiple priorities, and deliver timely, high-quality outputs.
  • Clear written and spoken communication in English, including the ability to explain technical concepts to non-technical audiences.

Internal applicants should be in their current job for at least 12 months, must meet performance standards and are not on formal corrective/disciplinary process (PIP), warning, final warning, or compliance warning letters within the last 12 months. Please inform your Manager or your Talent Partner before applying to any internal job opportunities.
Unless explicitly stated in the description, this role is hybrid with 40% of your time spent in the office, regardless of your current contractual agreement. If your current working arrangements differ, please contact your Talent Partner to discuss before submitting your application.
UCB is an equal opportunity employer. All employment decisions will be made without regard to any characteristic protected by applicable federal, state, or local law. UCB invites you to voluntarily self-identify during the application process. Provision of self-identification information is entirely voluntary and a decision to provide or not provide such information will not have any effect on your application for employment, your employment with UCB, or otherwise subject you to any adverse treatment. Any information you provide will be considered confidential and will be kept separate from your application and/or personnel file and will only be used in accordance with applicable laws, orders, and regulations.
Should you require any adjustments to our process to assist you in demonstrating your strengths and capabilities contact us on US-Reasonable_Accommodation@ucb.com for application to US based roles. Please note should your enquiry not relate to adjustments; we will not be able to support you through this channel.
Requisition ID: 93379
Recruiter: Kelly Dickinson
Hiring Manager: Baldur Magnusson
Talent Partner: Natacha Tassier
Job Level: MM II
Please consult HRAnswers for more information on job levels.

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