Data Science Intern
@ WillHire

Hybrid
$52,000
Hybrid
Intern
Posted 21 days ago

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Job Details

About WillHire

WillHire is a modern staffing and talent acquisition platform helping leading organizations find exceptional talent. We’re expanding into the Data Science vertical and are looking for curious, driven, and analytical minds to join our Data Science Internship Cohort.

Role Overview

As a Data Science Intern at WillHire, you will collaborate with our engineering and strategy teams to design data-driven solutions that power smarter hiring, workforce planning, and operational decision-making. This hands-on role involves working on real business datasets to build production-ready analytics models and dashboards.

Key Responsibilities

  • Collect, clean, analyze, and transform HR and recruitment datasets.
  • Build predictive models for talent forecasting and attrition risk.
  • Develop data visualizations, dashboards and reports using Python, SQL, and BI tools.
  • Perform exploratory data analysis to inform recruitment strategies.
  • Work with time-series and cohort data for trend analysis.
  • Deploy statistical and ML algorithms in scalable pipelines.
  • Communicate findings through clear visual and written formats to stakeholders.

Requirements

  • Pursuing or recently completed B.Tech/BE/M.Tech/MSc in Data Science, Computer Science, Statistics, or related fields.
  • Proficiency in Python and core libraries (Pandas, NumPy, Matplotlib/Seaborn, Scikit-learn).
  • Familiarity with SQL for querying relational datasets.
  • Sound understanding of ML fundamentals – supervised and unsupervised learning methods.
  • Strong statistics foundation including distributions, hypothesis testing, and probability.
  • Ability to interpret data, derive insights, and clearly present conclusions.
  • Strong communication skills, ownership mindset, and enthusiasm to learn.

Nice to Have (Bonus)

  • Knowledge of BI tools (Power BI, Tableau, Looker, Metabase).
  • Basics of cloud platforms (AWS, GCP, Azure) or Docker.
  • Prior exposure to HR analytics or recruitment datasets.

What You’ll Get

  • Practical exposure to solving real-world data problems in HR Tech.
  • Experience working on high-impact product features used by recruiters and hiring managers.
  • 1:1 mentorship by experienced data scientists and access to premium resources.
  • Internship Certificate & Letter of Recommendation upon successful completion.
  • Opportunity for a Pre-Placement Offer (PPO) at WillHire or client companies.

Hiring Process

  • Online Application: Submit CV, GitHub/Kaggle links, and a brief note on your interest and experience.
  • Technical Assessment: Assignment to test Python, SQL, EDA, or modeling approach.
  • Technical Interview: In-depth discussion (45 mins) on ML/stats understanding and problem-solving.
  • Managerial Interview: Evaluate communication skills, culture fit, and motivation.
  • Offer: Selected applicants receive the internship offer with stipend details and project allocation.
  • Onboarding: Orientation, project assignment, and setup with tools and mentors.

Compensation

Minimum stipend starts at $25/hour, with potential increases based on interview performance.

Key skills/competency

  • Python
  • SQL
  • Machine Learning
  • Data Cleaning
  • Data Visualization
  • EDA
  • Statistics
  • Predictive Modeling
  • HR Analytics
  • BI Tools

How to Get Hired at WillHire

🎯 Tips for Getting Hired

  • Research WillHire's culture: Explore their mission and recent news online.
  • Customize your resume: Highlight data science projects and skills.
  • Showcase technical skills: Emphasize Python, SQL, and ML expertise.
  • Prepare for interviews: Review ML algorithms and data analysis examples.

📝 Interview Preparation Advice

Technical Preparation

Review Python libraries usage.
Practice SQL queries on datasets.
Learn ML algorithm implementation.
Study data visualization techniques.

Behavioral Questions

Describe past data project challenges.
Explain teamwork in cross-functional settings.
Discuss learning from technical feedback.
Share experiences managing deadlines.

Frequently Asked Questions