Job Title: Data Scientist – AI Products & Deployment

Department: Technology / Data Science

Role Overview

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.

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, Dev Ops 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 (Tensor Flow, 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 Sage Maker, 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.

📌 Data Scientist – AI Products & Deployment (India)
🏢 PhillipCapital India
📍 India