This role involves working across the entire data science lifecyclefrom data exploration and modelling to GenAI integration and insight generation.

You will play a key role in designing, developing, and deploying data science solutions across various domains, including healthcare, finance, and enterprise analytics.

You will collaborate closely with cross-functional teams, including frontend developers, designers, product managers, and AI/ML specialists, to deliver high-performance, AI-integrated digital solutions.

This is an excellent opportunity for someone passionate about clean architecture, performance optimisation, and building intelligent, user-centric applications.

Responsibilities :

- Machine Learning and Data Analysis : Assist in developing ML models for tasks like classification, regression, clustering, and recommendation.

- Perform data preprocessing, cleaning, and exploratory analysis.

- Support feature engineering and model evaluation under the guidance of senior team members.

- Generative AI & NLP : Learn and experiment with LLMs and GenAI frameworks (e.g., OpenAI, Hugging Face, LangChain).

- Apply basic NLP techniques (tokenisation, text classification, sentiment analysis, entity recognition).

- Support the development of AI-powered applications like summarizers, Q& A bots, or report generators.

Requirements :

- 7-10+ years of experience (internships, projects, or academic exposure in GenAI).

- Proficiency in Python and key libraries (Pandas, NumPy, Scikit-learn).

- Basic understanding of statistics, probability, and ML algorithms.

- Exposure to NLP libraries (NLTK, spaCy, Hugging Face) is a plus.

- Familiarity with GenAI concepts (prompt engineering, fine-tuning) is an advantage.

- Knowledge of SQL (and basic NoSQL) databases.

- Exposure to cloud platforms (AWS, GCP, Azure) is desirable.

- Strong problem-solving mindset and eagerness to learn.

- Good communication skills and the ability to collaborate in a team.