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Data Science Internships Jobs (NOW HIRING)

Faire

Data Science Intern

San Francisco, CA · On-site

$75/hr

Data Science Internship - Fall 2026 Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e ...

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How much do data science internships jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data science internships in the United States is $105,861.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is a data science internship?

A Data Science Internship is a temporary position where students or recent graduates gain hands-on experience in data analysis, machine learning, and statistical modeling. Interns typically work with real-world datasets, build predictive models, and assist in data-driven decision-making processes. They may use programming languages like Python or R, tools such as SQL, and visualization libraries to communicate insights. This role helps develop technical and analytical skills while providing exposure to industry practices.

What skills and qualifications are needed for data science internships?

To excel in Data Science Internships, a solid understanding of statistics, programming (often in Python or R), and data analysis is typically required, often supported by progress toward a degree in a related field. Familiarity with tools like SQL, Jupyter notebooks, data visualization libraries, and sometimes cloud platforms or machine learning frameworks is common. Strong problem-solving abilities, attention to detail, and effective communication skills help interns succeed in team environments. These skills enable interns to analyze real-world datasets, communicate findings clearly, and contribute meaningful insights to organizational projects.

What do data science interns do?

Data Science Interns usually assist with tasks such as data cleaning and preprocessing, exploratory data analysis, developing and testing predictive models, and creating data visualizations to help teams make informed decisions. Interns often collaborate closely with data scientists, engineers, and business analysts, allowing them to contribute to larger, real-world projects while learning best practices. Daily responsibilities might also include attending team meetings, presenting results to stakeholders, and documenting their work. This hands-on experience allows interns to apply academic knowledge, build a professional portfolio, and prepare for future opportunities in the field.

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Data Science Internships jobs near you
Infographic showing various Data Science Internships job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $105,861 per year, or $50.9 per hour.

Data Science Intern

Faire

San Francisco, CA • On-site

$75/hr

Other

Re-posted 23 days ago

Job description

Data Science Internship - Fall 2026

Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e-commerce platforms and big-box stores. Our Data Science team builds and maintains the algorithmic systems - spanning search, personalization, recommendation, and ranking - that power our marketplace and help our customers thrive.

We are hiring Data Science interns across several teams and are looking for intellectually curious, self-directed problem solvers eager to work end-to-end on high-impact challenges, from data exploration to production-ready solutions.

Our internships are paid, 12-14 weeks in duration, with flexible start dates. Extensions are considered based on project scope and mutual interest.

Open Team

Search & Recommendation

  • Design and deploy state-of-the-art recommender systems that power ranking and discovery across the marketplace
  • Develop rich user and item representations through embeddings, sequence models, and graph-based methods
  • Build real-time and streaming data pipelines that enable dynamic, context-aware personalization at scale
  • Apply exploration-exploitation strategies - including contextual bandits and reinforcement learning - to optimize recommendations under uncertainty
  • Advance recommendation quality through improvements to diversification, novelty, and long-term user engagement
  • Own the full ML lifecycle: from problem formulation and modeling through offline evaluation and online experimentation

What You'll Do

  • Design, develop, and A/B test cutting-edge machine learning algorithms and analytical solutions, with guidance from senior technical leads
  • Communicate project objectives, methodologies, and results clearly to both immediate teammates and broader cross-functional stakeholders
  • Navigate the complexity of a two-sided marketplace, identifying and addressing the unique challenges that arise at the intersection of retailer and brand needs

What We're Looking For

All candidates must be currently enrolled or recently graduated Master's or PhD students in Computer Science, Operations Research, Statistics, Econometrics, or a related technical discipline. Beyond that, we're looking for team-specific experience:

Search & Recommendation Systems

  • Publications or submissions to top-tier venues such as KDD, RecSys, ICML, NeurIPS, WWW, or SIGIR
  • Experience with recommender systems (collaborative filtering, deep recommenders, ranking), representation learning and embeddings, sequential models (RNNs, Transformers for user behavior modeling), bandit and reinforcement learning methods, and large-scale retrieval and ranking systems
  • Familiarity with offline evaluation metrics (NDCG, MAP, recall) and online experimentation
  • Experience working with large-scale or production datasets

Pay rate:

San Francisco: the pay rate for this role is $75 USD per hour.

Actual hourly pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

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