Data Science Internship

As a Data Science intern at Emoolar Technology Private Limited, you will have the opportunity to work on cutting-edge projects in the fields of Machine Learning and Data Science.

You will gain hands-on experience in analyzing large datasets, developing predictive models, and extracting valuable insights to drive business decisions.

Your contributions will directly impact the company's success and help shape the future of our products and services. Key responsibilities: 1. Collaborate with cross-functional teams to identify business needs and develop data-driven solutions.

2. Clean, preprocess, and analyze data to uncover trends and patterns using statistical and machine learning techniques. 3. Build predictive models and algorithms to optimize processes and improve decision-making.

4. Interpret and communicate findings to non-technical stakeholders through visualizations and presentations. 5. Assist in the development and implementation of data science pipelines and tools.

6. Stay current with industry trends and best practices in data science and machine learning. 7. Contribute to a culture of innovation and continuous improvement within the data science team.

Who can apply: Only those candidates can apply who: • are available for the work from home job/internship • can start the work from home job/internship between 12th Sep'26 and 17th Oct'26 • are available for duration of 3 months • have relevant skills and interests • * Women wanting to start/restart their career can also apply.

Stipend: INR₹ 5,000 - 6,000 /month Deadline: 2026-10-12 23:59:59 Other perks: Certificate, Letter of recommendation, Flexible work hours, 5 days a week Skills required: Machine Learning and Data Science About Company: At Emoolar, we are a leading provider of comprehensive IT services tailored to meet the evolving needs of businesses in the digital age.

With a commitment to excellence and innovation, we deliver cutting-edge solutions that empower organizations to thrive in today's dynamic and competitive landscape.