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Seasonal Data Science Internships Jobs (NOW HIRING)

Faire

Data Science Intern

San Francisco, CA

$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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Seasonal Data Science Internships information

What are Seasonal Data Science Internships?

Seasonal Data Science Internships are temporary positions, typically offered during the summer or other academic breaks, that provide students or recent graduates with hands-on experience in data science. Interns work on real-world projects involving data analysis, machine learning, and statistical modeling, often under the guidance of experienced data scientists. These internships allow participants to apply classroom knowledge, gain practical skills, and build professional networks in the tech or analytics industry. They can also serve as a pathway to full-time employment after graduation.

What types of projects can a Seasonal Data Science Intern expect to work on, and how are these projects typically structured?

As a Seasonal Data Science Intern, you can expect to work on short-term, impactful projects such as data cleaning, exploratory data analysis, building predictive models, or supporting ongoing research. Projects are usually well-defined and time-bound to fit the internship duration, with clear objectives and guidance from a mentor or data science team. You'll often collaborate with other interns, data scientists, and sometimes cross-functional teams like engineering or business analytics, gaining exposure to real-world datasets and tools. Regular check-ins and presentations may be part of your workflow, offering opportunities for feedback and professional growth.

What are the key skills and qualifications needed to thrive as a Seasonal Data Science Intern, and why are they important?

To thrive as a Seasonal Data Science Intern, you generally need a strong background in statistics, data analysis, and programming skills in languages like Python or R, often supported by progress toward a degree in data science, computer science, or a related field. Familiarity with data visualization tools (e.g., Tableau, Power BI), machine learning libraries (e.g., scikit-learn, TensorFlow), and version control systems like Git is typically expected. Strong problem-solving abilities, attention to detail, and effective communication skills help interns stand out by enabling them to interpret data insights and work collaboratively. These skills are crucial for contributing meaningfully to projects, learning rapidly, and adapting to the fast-paced, project-driven nature of internships.
What cities are hiring for Seasonal Data Science Internships jobs? Cities with the most Seasonal Data Science Internships job openings:
What are the most commonly searched types of Data Science Internships jobs? The most popular types of Data Science Internships jobs are:
What states have the most Seasonal Data Science Internships jobs? States with the most job openings for Seasonal Data Science Internships jobs include:
Seasonal Data Science Internships jobs near you

Data Science Intern

Faire

San Francisco, CA

$75/hr

Other

Re-posted 19 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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