Job Summary
We are looking for an experienced Data Scientist to join our team and drive data-driven solutions across business and customer use cases. The ideal candidate will have strong expertise in Machine Learning, Python, Generative AI, LLMs, and RAG, with the ability to translate complex business problems into scalable analytical and AI solutions.
Key Responsibilities
- Develop, deploy, and maintain machine learning models for business and customer-focused use cases.
- Work on Generative AI, LLM, and RAG-based applications to solve complex business problems.
- Perform exploratory data analysis, feature engineering, model development, validation, and optimization.
- Design and implement solutions using NLP, predictive analytics, classification, regression, clustering, and recommendation techniques.
- Develop and optimize LLM prompts, embeddings, vector search, and retrieval pipelines.
- Build and evaluate RAG pipelines using appropriate frameworks and vector databases.
- Collaborate with data engineers, business teams, and stakeholders to understand requirements and deliver analytical solutions.
- Apply statistical methods and machine learning techniques to identify patterns, trends, and actionable insights.
- Monitor model performance and continuously improve model accuracy, scalability, and reliability.
- Contribute to the development of reusable AI/ML frameworks, methodologies, and best practices.
- Present analytical findings and model outcomes to technical and non-technical stakeholders.
Required Skills
- 3-8 years of experience in Data Science / Machine Learning / AI.
- Strong programming skills in Python.
- Strong understanding of Machine Learning algorithms and statistical concepts.
- Hands-on experience with Generative AI and Large Language Models (LLMs).
- Experience building RAG (Retrieval-Augmented Generation) solutions.
- Knowledge of Prompt Engineering, embeddings, vector databases, and semantic search.
- Experience with NLP, Deep Learning, and predictive modeling.
- Strong SQL skills and experience working with large datasets.
- Experience with ML/AI frameworks such as Scikit-learn, TensorFlow, PyTorch, LangChain, or similar frameworks.
- Understanding of model evaluation, experimentation, and performance optimization.
- Strong analytical, problem-solving, and communication skills.