Data Science Internship

Selected intern's day-to-day responsibilities include: We are looking for a hands-on Data Scientist Intern who is interested in solving real business problems using data, machine learning, and AI.

The intern will work on live datasets across domains such as manufacturing, healthcare/pharma, financial analytics, and enterprise decision intelligence.

The role will involve exploratory data analysis, feature engineering, predictive modelling, model evaluation, and increasingly, the use of LLMs and GenAI as part of modern data science workflows.

We are looking for someone who is strong in fundamentals, comfortable working independently with data, and willing to experiment, learn, and build. Key Responsibilities Clean, preprocess, validate, and analyze structured and semi-structured datasets.

Perform detailed exploratory data analysis (EDA) and identify patterns, relationships, anomalies, and data-quality issues. Develop and evaluate machine learning models for classification, regression, forecasting, clustering, and other business problems.

Perform feature engineering and identify relevant variables for modelling. Establish baselines and evaluate models using appropriate statistical and ML metrics.

Use Python and/or R for data analysis, visualization, statistical analysis, and modelling. Work with SQL and databases to extract and analyze data. Build clear visualizations and analytical summaries for technical and business users.

Experiment with LLMs/GenAI for activities such as data understanding, automated analysis, insight generation, and model-assisted workflows. Support development of reusable analytical pipelines and AI/ML components.

Work closely with senior data scientists, developers, and business teams on client and product initiatives. Clearly document datasets, assumptions, methodology, experiments, models, and findings.

Present findings in a simple and business-understandable manner. Required Skills Good working knowledge of Python. Familiarity with libraries such as: Pandas NumPy Scikit-learn Matplotlib / Seaborn Good understanding of: Statistics and probability Exploratory data analysis Regression and classification Feature engineering Model evaluation Basic knowledge of SQL and relational databases.

Ability to understand unfamiliar datasets and independently investigate them. Strong analytical and problem-solving skills. Ability to clearly explain analytical findings.

Good to Have Experience with R and statistical modelling. Exposure to time-series analysis and forecasting. Familiarity with XGBoost, LightGBM, CatBoost or similar ML libraries.

Exposure to Generative AI, LLMs, prompt engineering, RAG, or AI agents. Familiarity with open-source LLMs such as Qwen, Llama, or similar models. Experience using APIs and integrating AI/ML models into applications.

Familiarity with Git/GitHub or GitLab. Exposure to cloud environments, Jupyter/JupyterHub, Docker, or similar development environments. Educational Qualification Bachelor's or Master's degree in: Computer Science Data Science / Artificial Intelligence Statistics Mathematics Engineering Econometrics / Operations Research Or another quantitative discipline Candidates with strong academic, internship, Kaggle, research, or personal projects in data science and machine learning are encouraged to apply.

What We Look For More than certifications, we look for candidates who can take a dataset, understand it, ask the right questions, analyse it systematically, build appropriate models, and explain what the results mean.

Candidates should be comfortable learning new techniques and working on problems where the solution may not be predefined. Internship Exposure Selected interns will get an opportunity to work on: Real-world enterprise and client datasets EDA and automated analytics Predictive and machine learning models Forecasting and decision intelligence GenAI and LLM-assisted analytics AI agents and intelligent workflows Production-oriented AI/ML use cases Strong performers may be considered for longer-term opportunities with the organization.

Who can apply: Only those candidates can apply who: • are available for full time (in-office) internship • can start the internship between 29th Sep'26 and 3rd Nov'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₹ 10,000 - 11,997 /month Deadline: 2026-10-29 23:59:59 Other perks: Certificate, Letter of recommendation Skills required: Python, SQL, Statistical Modeling, Machine Learning, Analytical Thinking, Problem Solving, Statistics, R Programming, Effective Communication, Data Analysis, Feature Engineering, Model Evaluation, Probability and Python Libraries Other Requirements: • 1.

Who have passed masters in DS. About Company: Aaum Research and Analytics, founded by an IIT Madras alumnus, brings extensive global business experience & works with Fortune 100 companies in North America and the Asia Pacific.

Established at IIT Madras ecosystem with a focus on researching and devising sophisticated analytical techniques to solve the pressing business needs of corporations ranging from travel, healthcare, entertainment, FMCGs, finance, insurance, retail, and telecom.

geniSIGHTS is a subsidiary of Aaum Research and Analytics.