Data Scientist

Location

The successful candidate shall be placed at Pune Location. It is a Full-time Job, “No” remote work. Data Scientist (GenAI/ML,Python, FastAPI/Flask) willing to work on a 6 to12-months contract may apply.

Experience

Candidates should have experience between 3-6 years

Role Description

About the Role

We are looking for a skilled and motivated Data Scientist with strong experience in Python, Machine Learning, and Generative AI, along with hands-on exposure to Flask and FastAPI for building and deploying scalable data-driven applications. The ideal candidate will work closely with cross-functional teams to design, develop, and deploy intelligent solutions that drive business value.

Key Responsibilities

- Design, develop, and deploy machine learning and generative AI models for real-world business problems. - Build and expose ML/AI models using RESTful APIs with Flask and FastAPI. - Perform data analysis, feature engineering, model training, validation, and optimization. - Work on end-to-end ML pipelines, from data ingestion to model deployment and monitoring. - Collaborate with product managers, engineers, and stakeholders to translate business requirements into technical solutions. - Optimize model performance, scalability, and reliability in production environments. - Stay updated with the latest advancements in ML, Generative AI, and AI frameworks. - Document models, APIs, workflows, and best practices.

Required Skills & Qualifications

- 3–6 years of hands-on experience as a Data Scientist or similar role. - Strong proficiency in Python. - Solid experience with Machine Learning algorithms (supervised, unsupervised, and deep learning). - Practical exposure to Generative AI (LLMs, embeddings, prompt engineering, or fine-tuning). - Experience building APIs using Flask and/or FastAPI. - Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. - Experience with common ML libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, etc.). - Good understanding of software engineering best practices and version control (Git).

Nice to Have

- Experience with cloud platforms (AWS, Azure, or GCP). - Knowledge of MLOps tools and CI/CD pipelines. - Exposure to vector databases, RAG architectures, or AI agents. - Familiarity with Docker/Kubernetes. - Strong communication and problem-solving skills.