Data Engineering: Gather and integrate data from multiple sources, performing data cleaning and transformation to ensure accuracy, reliability, and readiness for analysis and AI model training.
Data Analysis & AI-Driven Insights: Analyze datasets using statistical methods and AI tools to uncover trends, patterns, and predictive insights that inform strategic business decisions.
Reporting and Visualization: Design and develop interactive reports, dashboards, and data visualizations that effectively communicate findings and AI-generated insights to stakeholders.
AI & Machine Learning Development: Support the development, testing, and optimization of machine learning models and AI algorithms to address specific business challenges and opportunities.
Data Governance & Stewardship: Collaborate with data stewards to maintain data quality, support governance initiatives, and ensure data integrity across analytics and AI systems.
Data Policy & Standards: Assist in developing and implementing data governance policies, standards, and procedures that support both traditional analytics and AI/ML initiatives.
Data Quality & Validation: Monitor and assess data quality across systems, implementing validation checks to ensure consistency and reliability for analytics and AI applications.
Research & Innovation: Explore emerging data technologies, AI tools, and best practices to enhance analytical capabilities and drive innovation in data-driven solutions.
Cross-Functional Collaboration: Partner with team members and stakeholders across departments to understand data requirements and deliver support for analytics and AI-powered projects.
Documentation & Knowledge Management: Document processes, methodologies, model performance, and insights to ensure knowledge retention and facilitate team collaboration.
Continuous Learning: Actively develop skills in data analysis, AI/ML techniques, and industry trends through training, self-study, and hands-on project experience.
About You:
Currently pursuing a MTECH/BTECH degree with an expected completion in 2026/2027 in a technical field such as Data and Analytics, Data Science.
Proficient in programming languages such as Python/SQL.
Familiarity with data visualization tools (e.g., Tableau, Power BI).
Analytical Thinking: Strong analytical skills to solve problems and make data-driven decisions.
Attention to Detail: Precision in analyzing data and ensuring accuracy in reporting.
Communication Skills: Ability to communicate complex data insights in a clear and concise manner to both technical and non-technical stakeholders.
Teamwork: Ability to work collaboratively within a team environment.
Curiosity and Eagerness to Learn: Willingness to learn new tools and techniques in the field of data and analytics.
About the role:
Hands-On Experience: Provide real-time projects that allow interns to apply their academic knowledge and gain practical skills in data and analytics.
Mentorship and Guidance: Pair interns with experienced mentors who can offer guidance, support, and insights into the field of data analytics.
Skill Development: Offer training sessions, workshops, and access to online courses to help interns enhance their technical and analytical skills.
Exposure to Tools and Technologies: Give interns the opportunity to work with industry-standard tools and technologies, such as Python, R, Fabric, SQL, and data visualization software.
Collaborative Environment: Foster a supportive and inclusive workplace where interns can collaborate with team members and contribute ideas.
Feedback and Evaluation: Offer regular feedback and performance evaluations to help interns understand their strengths and areas for improvement.