Job Overview
Role: Intern Data Science Location: Hyderabad Experience: 0-0 Qualification: Graduate or postgraduate qualification in a quantitative discipline Key Skills: Statistical Modeling, Machine Learning, Predictive Analytics, Generative AI, Workforce Analytics, Regression, Classification, Clustering, Design of Experiments, Statistical Inference, Data Mining, EDA, Feature Engineering, Data Visualization, Dashboards
Job Description
This is an early-career opportunity for candidates interested in Data Science, Machine Learning, Predictive Analytics, Generative AI and workforce analytics. The position is based in Hyderabad, India and is part of the People & Organization division under the Human Resources business unit. Interns will work on statistical models, machine learning, dashboards, exploratory data analysis and LLM-based solutions with visibility to stakeholders and business leaders.
Roles and Responsibilities
- Apply data science techniques to employee engagement challenges.
- Support recruitment optimization and predictive workforce planning initiatives.
- Develop models, dashboards and analytical frameworks that support enterprise-level decisions.
- Collaborate on high-impact projects with stakeholders and leaders.
- Support research and development of new algorithms, statistical models, methods and business models.
- Provide insights from structured and unstructured data.
- Conduct statistical and machine learning analysis for business problems.
- Develop predictive models for talent acquisition, employee experience, location strategy and workforce planning.
- Build self-service dashboards and visualizations for stakeholders.
- Perform data mining, exploratory data analysis and feature engineering.
- Use Generative AI to support personalized employee experiences and HR workflows.
- Explore and prototype LLM-based workforce analytics use cases.
Skills and Eligibility Criteria
Educational Background: Graduate or postgraduate qualification in a quantitative discipline. Graduation or post-graduation from a top-tier university is mentioned as preferred.
Experience: Relevant experience or exposure in Data Science (for early-career candidates).
Mandatory Technical Skills:
- Strong understanding of statistical modeling and machine learning techniques
- Regression (Generalized Linear Models (GLM), non-linear regression)
- Classification (Decision trees, Random Forest, Boosting, SVM, CART)
- Clustering (Unsupervised learning and segmentation techniques)
- Design of Experiments (Experimental design and analysis)
- Statistical Inference (Applying statistical methods to draw conclusions from data)
- Machine Learning (Building and evaluating predictive models)
- Data mining
- Exploratory Data Analysis (EDA)
- Feature engineering
- Predictive modeling
- Data visualization
- Dashboard development
- Structured and unstructured data analysis
- Generative AI for employee experiences
- AI-assisted HR workflows
- Decision-support applications
- LLM-based workforce analytics
- Prototyping AI use cases