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Description:
We are seeking a Data Scientist who is passionate about transforming raw data into intelligent business insights and building models that power real-world decision-making. This role involves working across the entire data science lifecycle- from 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:
- 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.
- 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.
- Gain exposure to model deployment workflows and MLOps tools (MLflow, SageMaker, Vertex AI, etc. ).
- Work with APIs and cloud environments to integrate data science solutions.
- Assist in monitoring and maintaining model performance.
Requirements:
- 3-4 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 ability to collaborate in a team.
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