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., Num Py, Pandas, Scikit-learn, Tensor Flow, 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.