Job Title: Data Scientist – AI Products & Deployment

Technology / Data Science

Phillip Capital is seeking an experienced Data Scientist with a robust focus on AI product lifecycle management . The ideal candidate should have design and build advanced AI models and also possess the engineering rigor to deploy, scale, and maintain these solutions in both cloud-based and on-premise server environments. You will bridge the gap between data science research and production-grade software engineering.

AI Product Development: Design, develop, and validate machine learning and deep learning models tailored to financial and operational use cases.

End-to-End Deployment: Own the deployment pipeline for AI models, ensuring seamless integration into existing systems via APIs, microservices, or embedded applications.

Hybrid Infrastructure Management:

Deploy and optimize models on major cloud platforms (e.g., AWS, Azure, GCP).

Manage and secure model deployments on on-premise servers , ensuring compliance with data sovereignty and security protocols.

Collaboration:



Work closely with software engineers, DevOps teams, and business stakeholders to translate business problems into scalable AI solutions.

Performance Optimization: Optimize model inference speed and resource utilization for both cloud and on-premise environments.

Education: B.Tech in Computer Science, Data Science, Statistics, or a related field.

Experience: 3+ years of experience in data science with a proven track record of shipping AI products to production.

Proficiency in Python, AI system design

Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).

Experience with cloud AI services (AWS SageMaker, Azure ML, GCP Vertex AI).

Experience deploying models on Linux-based on-premise servers (including containerization and orchestration).

Experience in the financial services or fintech industry.

Experien

📌 Data Scientist (Mumbai)
🏢 PhillipCapital India
📍 Mumbai