
Trainee - Data Science and Engineering (10)
18 hours ago
Position Summary
As a Trainee Data Science & Engineering, you will undergo structured training and gain hands-on experience in data analysis, statistical modelling, and machine learning. Under the mentorship of experienced data scientists and architects, you will work on solving real business challenges using modern data science tools and techniques.
This role is ideal for recent graduates who are passionate about AI, automation, and machine learning, and eager to launch their careers in data science and engineering.
Key Responsibilities
- Create data visualizations and dashboards using tools such as Power BI, Tableau, or Python libraries
- Perform analytical and machine learning tasks including regression, time series forecasting, and decision trees
- Support senior data scientists in developing models and performing statistical analysis
- Work closely with solution architects in planning, estimation, and agile team activities
- Participate in R&D initiatives to explore new tools, models, and use cases
- Document project outcomes, learnings, and methodologies clearly and effectively
- Continuously build skills through mentorship, online resources, and project experience
Qualifications & Skills
- Bachelors degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related field.
- Strong academic background in mathematics, statistics, or data-related subjects.
- Basic understanding of Python/R, SQL/NoSQL, data visualization concepts and Web development concepts (HTML, CSS, Javascript).
- Should be able to understand, process and analyze data (internal as well as external) to extract useful information, patterns, insights related to the business objective
- Curiosity to explore data and learn new analytical tools and methods.
- Strong problem-solving, logical thinking, and communication skills.
- Eagerness to learn and work in a collaborative, fast-paced environment.
What We Offer
- Hands-on training and mentorship from experienced professionals.
- Exposure to real-world data projects and enterprise-level challenges.
- Opportunity to convert to full-time employment based on performance.
- Supportive, learning-focused work culture with access to learning resources.
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