Job Summary

We are seeking a seasoned Senior Data Scientist with 15+ years of experience in developing and deploying machine learning solutions. The ideal candidate should have hands-on expertise in MLOps (at least two end-to-end production deployments), solution architecture, and experience with one major cloud platform (AWS, Azure, or GCP) is an added advantage. Strong skills in Python, SQL, PySpark, Generative AI (GenAI), and NLP are required.

Key Responsibilities

• Architect and deploy scalable ML/AI solutions, including MLOps pipelines for CI/CD, model monitoring, and governance.
• Lead the design and development of GenAI and NLP solutions for applications such as text summarization, conversational AI, and entity recognition.
• Build and optimize data pipelines using PySpark and SQL for large-scale data processing.
• Scalable ML development and deployment
• Collaborate with stakeholders to align AI initiatives with business goals and mentor junior team members.

Qualifications & Skills

• Bachelors degree with 10-12 years of exp in Data, AI, ML
• Programming: Python (Pandas, NumPy, PyTorch, TensorFlow), SQL.
• MLOps: Experience with tools like MLflow, Kubeflow, Docker, Kubernetes, and CI/CD pipelines.
• Generative AI & NLP: Expertise in transformer models (e.g., GPT, BERT), Hugging Face, and LangChain.
• Data Engineering: Proficient in PySpark and distributed data processing.
• Cloud Platforms: Proven experience with one major cloud platform (AWS, Azure, or GCP) is an added advantage

Mandatory Skills

• Expertise in data architecture, modeling (dimensional, relational, etc.), and cloud/on-prem hybrid environments.
• Strong in Python, PySpark; proficiency in SQL.
• Experience with entity resolution, data governance tools.
• Exposure to GenAI, ML, or LLM integration is a plus.
• Familiarity with financial products, GL data, or finance operations preferred