Job Overview
Role: Data Science Intern Location: Remote Experience: 0-0 Qualification: Any Graduate / B.E / B.Tech / B.Sc / BCA / M.Sc / MCA / Data Science Freshers & Students Key Skills: Python, R, SQL, Data Visualization, Machine Learning
Job Description
Astreya, a global leader in IT solution services and technology-driven operations, has announced an off-campus hiring drive under Astreya Internship 2026. Astreya is inviting online applications for the position of Data Science Intern. As a Data Science Intern at Astreya, you will work closely with experienced data engineers and cross-functional business teams to solve real-world problems through data analysis, machine learning models, and interactive visualizations.
Roles and Responsibilities
- Data Preparation & Exploration: Assist in collecting, cleaning, and preprocessing datasets from diverse sources; perform exploratory data analysis (EDA) to discover trends.
- AI & Model Development: Support the development, testing, and tuning of machine learning models for tasks such as classification and predictive forecasting.
- Problem-Solving: Apply analytical thinking to resolve business challenges like customer segmentation, campaign evaluation, and process optimization.
- Visualization & Reporting: Create simple dashboards and reports to communicate analytical insights to stakeholders.
- Collaboration & Communication: Work alongside product, business, and engineering teams to interpret project goals and present findings clearly to technical and non-technical audiences.
- A/B Testing: Learn to design, execute, and analyze controlled experiments to test business hypotheses.
Skills and Eligibility Criteria
Educational Background: Any Graduate / B.E / B.Tech / B.Sc / BCA / M.Sc / MCA / Data Science Freshers & Students.
Experience: Freshers / Interns.
Mandatory Technical Skills:
- Familiarity with Python or R for data manipulation and analysis tasks.
- Ability to write fundamental SQL queries to extract, filter, and aggregate relational data.
- Good understanding of basic statistics including distributions, averages, standard deviations, and correlations.
- Core knowledge of data mining, basic machine learning algorithms, and exploratory visualization tools.
Competencies:
- Willingness to learn and explore tools like Tableau or Power BI under guided mentorship.
- Strong logical reasoning and methodical problem-solving capability.
- A keen eye for pattern recognition, anomalies, and data trends.
- High curiosity, self-drive, and eager initiative to ask questions and learn emerging technologies.