Data Science Intern
Dexter's Tech
Job Overview
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Job Description
About Data Science Intern
Dexter’s Tech empowers aspiring data professionals by providing practical, industry-relevant experience in data science. Interns will build strong foundations in analytics, statistics, and machine learning through live projects aligned with real-world business and technology challenges.
Opportunity & Benefits
- Performance-based stipend up to ₹7,499
- Swags and goodies
- Internship Certificate
- Letter of Recommendation based on performance
- Potential full-time role based on performance
- Hands-on experience with real-world data science projects
Roles & Responsibilities
- Collect, preprocess, and analyze large datasets
- Perform Exploratory Data Analysis (EDA) to uncover insights
- Build predictive models and machine learning algorithms
- Create data visualizations and dashboards
- Collaborate with cross-functional teams for data-driven solutions
Requirements
- Currently enrolled in or graduated from relevant fields
- Proficiency in Python or R
- Familiarity with scikit-learn, TensorFlow, or PyTorch preferred
- Experience with visualization tools like Tableau, Power BI, or Matplotlib
- Strong analytical, problem-solving, and communication skills
What You Will Gain
- Real-world exposure to data science workflows
- Performance-based stipend up to ₹7,499
- Swags and goodies
- Internship Certificate and Letter of Recommendation
- Opportunity to build a strong data science portfolio
- Potential full-time role
How to Apply
Submit your resume and cover letter with the subject line: "Data Science Intern Application" before the deadline on 12th February 2026.
Equal Opportunity Statement
Dexter’s Tech is an equal opportunity organization and encourages applications from candidates of all backgrounds.
Key skills/competency
- Data Analysis
- Machine Learning
- Python
- R
- EDA
- Data Visualization
- Predictive Modeling
- Statistics
- Tableau
- Problem-solving
How to Get Hired at Dexter's Tech
- Research Dexter's Tech culture: Study mission, values, and employee reviews.
- Customize your resume: Highlight data science and analytics skills.
- Prepare real-world examples: Showcase previous data projects and problem solving.
- Practice technical interviews: Focus on Python, ML, and EDA.
- Follow application instructions: Use specified email subject line.
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