Data Scientist - AI Products & Deployment

PhillipCapital India · India

Job Title: Data Scientist – AI Products & Deployment

Department:  Technology / Data Science 

Role Overview

Phillip Capital is seeking an experienced Data Scientist with a strong 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.

Key Responsibilities

• 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.

Required Qualifications

• 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.
• Technical Skills:
• Proficiency in Python, AI system design
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

Other optional skillsets :

• 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).
• Soft Skills:  Strong problem-solving abilities, attention to detail, and excellent communication skills for cross-functional collaboration.

Preferred Qualifications

• Experience in the financial services or fintech industry.
• Experience with CI/CD pipelines for machine learning models.
• Familiarity with edge AI or low-latency deployment scenarios.