Data Scientist

Job Description

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.