Data Science Intern

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About the Opportunity

Job Nexus India is listing a Data Science Internship on behalf of one of our hiring partners. This role is intended for candidates interested in gaining hands-on experience in data science and machine learning while working on real-world datasets and applied projects.

The internship offers exposure to analytical workflows, model development, and collaborative problem-solving in a professional environment.

Key Responsibilities

• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Assist in data collection, cleaning, preprocessing, and validation.
• Develop and test machine learning models using appropriate algorithms.
• Evaluate model performance and refine models to improve accuracy and efficiency.
• Collaborate with cross-functional teams to understand project requirements.
• Create clear data visualisations, reports, and documentation to communicate insights.
• Participate in code reviews and follow established development best practices.
• Support the development of data-driven solutions for practical use cases.
• Stay updated with current tools, techniques, and advancements in data science and machine learning.

Requirements

• Strong interest in data science, machine learning, or applied analytics.
• Basic knowledge of Python and commonly used data science libraries.
• Understanding of statistics, probability, and analytical concepts.
• Familiarity with data preprocessing and exploratory analysis techniques.
• Ability to interpret results and communicate insights clearly.
• Exposure to machine learning algorithms is an advantage.
• Strong problem-solving skills and attention to detail.
• Ability to work independently in a remote environment and collaborate with teams.

Who Can Apply

• College students
• Fresh graduates
• Early-career professionals interested in data science

What This Internship Offers

• Hands-on experience with real-world data science projects
• Exposure to industry-relevant tools and workflows
• Opportunity to strengthen technical and analytical skills
• Competitive stipend based on skills and performance
• Fully remote work environment