Data Science Intern

Job Description

About the Company: HireShire

HireShire is a cutting-edge platform specializing in staffing and talent acquisition. Its core mission is to assist leading organizations in identifying and securing exceptional talent. The company is currently expanding its operations into the Data & Analytics vertical, seeking to integrate data-driven solutions into its core offerings.

—

Job Description: Data Science Intern (Data Science Internship Cohort)

Role Overview:
The Data Science Intern at HireShire will play a pivotal role in the newly formed Data & Analytics vertical. This is a highly hands-on position where the intern will collaborate closely with engineering and strategy teams. The primary goal is to design and implement data-driven solutions aimed at optimizing various aspects of the hiring process, workforce planning, and overall operational decision-making. Interns will work with real business datasets to build and deploy production-ready analytics models and dashboards.

Key Responsibilities:

• Data Management: Collect, clean, analyze, and transform both structured and semi-structured HR and recruitment datasets.
• Predictive Modeling: Develop predictive models for critical areas such as talent forecasting, assessing attrition risk, and generating candidate success scores.
• Data Visualization: Create insightful data visualizations, dashboards, and reports using tools like Python, SQL, and various BI tools.
• Exploratory Data Analysis (EDA): Conduct comprehensive EDA to uncover hidden insights that can inform and refine recruitment strategies.
• Trend Analysis: Work with time-series and cohort data to perform trend analysis and monitor key performance metrics.
• Algorithm Deployment: Deploy statistical and Machine Learning (ML) algorithms (including regression, clustering, and classification) within scalable data pipelines.
• Communication: Effectively communicate complex findings and recommendations to stakeholders through clear visual and written formats.

Requirements:

• Education: Currently pursuing or recently completed a B.Tech/BE/M.Tech/MSc degree in Data Science, Computer Science, Statistics, or a closely related quantitative field.
• Programming Proficiency: Demonstrated proficiency in Python and its core data science libraries, including Pandas, NumPy, Matplotlib/Seaborn, and Scikit-learn.
• Database Skills: Familiarity with SQL for querying and manipulating relational datasets.
• Machine Learning Fundamentals: A solid understanding of Machine Learning fundamentals, encompassing both supervised and unsupervised learning methods.
• Statistical Foundation: Strong foundational knowledge of statistics, including distributions, hypothesis testing, and probability theory.
• Analytical Acumen: The ability to interpret data, derive meaningful insights, and present conclusions clearly and concisely.
• Soft Skills: Strong communication skills, a proactive ownership mindset, and genuine enthusiasm for learning and problem-solving.

Nice to Have (Bonus Skills):

• Business Intelligence Tools: Knowledge of BI tools such as Power BI, Tableau, Looker, or Metabase.
• Cloud & Containerization: Basic understanding of cloud platforms like AWS, GCP, or Azure, or experience with Docker.
• Domain Specific Experience: Prior exposure to HR analytics or recruitment-specific datasets.

What You’ll Get:

• Real-World Experience: Practical exposure to solving high-impact data problems within the dynamic HR Tech industry.
• Product Impact: The opportunity to work on significant product features that will directly benefit recruiters and hiring managers.
• Mentorship: 1:1 mentorship from experienced data scientists and access to premium learning resources.
• Recognition: An Internship Certificate and a Letter of Recommendation upon successful completion of the internship.
• Career Opportunity: A potential Pre-Placement Offer (PPO) at HireShire or with one of its client companies.

Hiring Process:

1. Online Application: Submit your CV, links to your GitHub/Kaggle profiles, and a brief note outlining your interest and relevant experience.
2. Technical Assessment: Complete an assignment designed to evaluate your skills in Python, SQL, EDA, or your approach to modeling.
3. Technical Interview: An in-depth 45-minute discussion focusing on your understanding of ML/statistics and problem-solving abilities.
4. Managerial Interview: An evaluation of your communication skills, cultural fit within the team, and motivation for the role.
5. Offer: Selected applicants will receive the internship offer, including stipend details and project allocation.
6. Onboarding: An orientation session, project assignment, and setup with necessary tools and mentors.

Stipend:
The minimum stipend for this internship starts at $19 per hour, with the possibility of a higher rate based on your performance during the interview process.