Data Science Intern

About the Role

Key Responsibilities

• Explore and examine data from multiple and diverse data sources.
• Perform conceptual modelling, statistical analysis, predictive modelling, and optimization.
• Clean, normalize, and transform datasets.
• Develop hypotheses and validate them through carefully designed experiments.
• Help build ETL workflows (Extract, Transform, Load) for data from different sources.
• Connect processed data with existing systems and datasets.
• Ensure data integrity and security.
• Experiment with different approaches, analyze results, and improve models based on user feedback.
• Contribute to projects that support real business requirements.

Required Qualifications & Eligibility

• Bachelor's or Master's degree in any STEM field.
• Educational background in Data Science or a related technical discipline is relevant to the role.
• Experience or understanding of solving complex problems using data science techniques.
• Understanding of how machine learning models work and why they produce particular results.
• Knowledge of probability theory, statistical inference, and linear algebra.
• Knowledge of machine learning tasks such as classification, prediction, and clustering.
• Ability to adapt quickly, experiment, and learn challenging concepts.
• Good communication and teamwork skills.
• Involvement in data science communities or platforms such as Kaggle, Numerai, or OpenML is encouraged.

Required Technical Skills & Tools

• Programming: Python, Git.
• Statistics & Mathematics: Probability Theory, Statistical Inference, Linear Algebra.
• Machine Learning: Classification, Prediction, Clustering, Statistical Modelling.
• Deep Learning: Neural Network (NN) Model Architectures.
• Python Libraries: NumPy, pandas, scikit-learn, Keras, TensorFlow, PyTorch.
• Generative AI & NLP: LangChain, Unsloth, Hugging Face.
• Data Processing: Data Cleaning, Normalization, Transformation, ETL Workflows.
• Research: Understanding of current Machine Learning and Artificial Intelligence research literature.

Preferred Qualifications

• Participation in data science competitions or communities such as Kaggle, Numerai, and OpenML.
• Knowledge of quantitative investment strategies.
• Interest in financial modelling and risk management.
• Familiarity with Generative AI and modern machine learning frameworks.
• Intellectual curiosity and willingness to learn advanced technical concepts.

Benefits & Perks

• Opportunity to work on real-world projects in the Global Markets – Data & AI Lab.
• Exposure to financial data science, quantitative modelling, and AI research.
• Opportunity to take ownership of one or more project topics.
• Experience working with diverse datasets and advanced machine learning techniques.
• Opportunity to see how developed solutions are used by business teams.
• Not specified.

Job Title

Company

Company Website

Category

Work Mode

• Not specified
• Employment Type: Internship

Experience Level

Location

Salary

Official Application URL

Duration

• 6 months.
• Starting date: Flexible; earlier joining is preferred.

Department

• Front Office Support.
• Business Line: Global Markets – Data & AI Lab.

Location

• Bengaluru, India.
• Reference Number: 1234567890100124831.
• Project allocation will depend on the candidate's skill set and business requirements.

Example Project Areas:

• Predicting products likely to interest a particular client.
• Automated generation of market commentary.
• Optimal risk management of Interest Rate Swap risk.
• Regime disentanglement for financial mixture-of-experts models.
• Generative modelling for model control.
• Transformers for quantitative investment strategies.