Kimberly-Clark is hiring an Analytics and Data Science Trainee for its Pune Kharadi Hub. The role provides end-to-end analytical support for GBS and Enterprise Projects through GBS, with a focus on data science, machine learning, and data cleansing.
Job Details
| Job Details | Information |
|---|---|
| Company | Kimberly-Clark |
| Position | Analytics and Data Science Trainee |
| Location | Pune Kharadi Hub |
| Employment Type | Full Time |
| Worker Type | Employee |
| Worker Sub-Type | Fixed Term |
| Job Requisition ID | 887306 |
| Application Deadline | September 30, 2026 |
Position
Analytics and Data Science Trainee
The selected candidate will support analytics and data science initiatives that help the business make data-driven decisions. The position focuses on data collection and cleaning, machine learning, exploratory data analysis, collaboration, and data visualization.
Responsibilities
- Assist in gathering, cleaning, and preprocessing data for analysis.
- Support the development of predictive models and algorithms.
- Conduct exploratory data analysis to identify trends, patterns, and anomalies.
- Work with data scientists and cross-functional teams to understand data requirements and implement solutions.
- Create visualizations and reports to communicate analytical findings.
- Provide end-to-end analytical support for GBS and Enterprise Projects through GBS.
Eligibility & Qualifications
Candidates should have:
- A Bachelor’s degree in Computer Science or a related quantitative field, with a focus on data science or analytics.
- Strong oral and written communication skills.
- Attention to detail.
- Ability to work through challenging situations or complex problems to achieve goals.
- Ability to manage and prioritize multiple projects.
- Ability to provide stakeholder updates and communications.
- Ability to collaborate effectively with colleagues, customers, and stakeholders from diverse backgrounds.
Required Skills
- Machine learning
- Data science
- Data cleansing
- Data collection and preprocessing
- Predictive model development
- Exploratory data analysis
- Data visualization
- ML system building, training, and deployment
- Data ingestion
- Model training and ongoing validation
- LLM-based workflows
- Power BI
- Analytical problem-solving
- Stakeholder communication
Application Details


