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JData Science Manager

Job Summary:

We are looking for a seasoned Data Science Manager with a minimum of 10 years of experience in Data Science and Machine Learning to lead our AI team. The ideal candidate will have a strong background in NLP, Transformers, Generative AI, Agentic Frameworks, Responsible AI and MLOps, as well as experience in deploying AI solutions across various cloud platforms. This role requires a combination of technical acumen, leadership skills, and a strategic mindset to drive AI initiatives that align with our business objectives.

Key Responsibilities:

• Leadership: Direct and support the AI team in developing and implementing advanced AI/ML solutions, ensuring projects align with the company's strategic goals.
• Project Management: Oversee the entire lifecycle of AI projects, from ideation to deployment, prioritizing tasks, and managing resources to meet deadlines and deliverables.
• Technical Mastery: Utilize expertise in Python, NLP, Transformers, and Generative AI to lead technical innovation and maintain high standards of excellence within the team. Having experience building Gen AI Agent and multi-agents leveraging any of the frameworks like Langgraph, Autogen, CrewAI, swarms , autonomous agent. 
• Cloud and MLOps Integration: Leverage cloud platforms such as AWS for deployment and incorporate MLOps practices leveraging Sagemaker, bedrock to enhance model development, deployment, and monitoring.
• System Architecture: Architect scalable, reliable, and high-performing AI systems that integrate seamlessly with existing infrastructure.
• Stakeholder Collaboration: Engage with stakeholders to convert business challenges into analytical questions, fostering a data-driven culture and driving impactful solutions.
• Team Development: Mentor team members, promote professional growth, and cultivate a culture of innovation and continuous improvement.
• Ethical AI Implementation: Uphold ethical standards in AI practices, ensuring models are fair, transparent, and accountable.
• Effective Communication: Develop and deliver clear, concise presentations to communicate complex technical details to diverse audiences, facilitating understanding and buy-in.

Requirements:

• Degree in Computer Science, Engineering, or a related technical field at the bachelor's or master's level; candidates with a Ph.D. will be given preference.
• At least 10 years of professional experience in the realm of Data Science and Machine Learning, including a leadership role with a documented history of success.
• Expertise in Python programming and experience with AI/ML libraries such as TensorFlow or PyTorch.
• Comprehensive understanding of Natural Language Processing (NLP) and hands-on experience with Transformer architectures.
• Proficient in leveraging AWS cloud platforms for the deployment of AI-driven solutions. Manage AWS cloud infrastructure and services including S3, EC2, Lambda, RDS, Glue, Sagemaker, EMR, and Step Functions to build and deploy scalable machine learning models.
• Solid grasp of MLOps concepts and practical experience with tools such as Docker, Kubernetes, and Git for operational efficiency.
• Capable of architecting and executing CI/CD workflows and managing infrastructure as code using tools like Terraform or AWS CloudFormation.
• Exceptional problem-solving abilities, analytical mindset, and effective communication skills.
• Established expertise with a minimum of 8 years in a technical capacity concentrating on AI/ML applications.
• Deep knowledge of AI/ML frameworks, NLP techniques, and Transformer-based model implementations.
• Proficiency in MLOps methodologies, including familiarity with LLMOps.
• Experience in developing APIs using frameworks such as FastAPI.
• Understanding of container orchestration using AWS EKS and familiarity with infrastructure frameworks like Bedrock.
• Oversee ethical AI practices, ensuring fairness, accountability, and transparency in AI systems.
• Exposure in AI governance, implementing and monitoring responsible AI frameworks.
• Manage risk and compliance with regulatory and ethical standards for AI deployment.
• Exposure ethical decision-making in AI development and operational processes.

Technical Skills:
 

Mandatory:

• Experience in end to end GenAI, NLP and AI/ML projects (design to implement to deploy) in banking industry
• Platform experience like Azure/AWS/GCP/Custom
• AI Strategy - Enterprise Patterns and Approach
• LLM Architecture and models, AI/ML models
• Prompt Strategies, Advance RAG Strategies, Fine Tuning Strategies
• Vector DB/Graph DB
• EDA and Data pipelines
• Agentic frameworks like crew, autogen, langgraph, swarms, autonomous agent any Agentic framework

Good to have:

• Multi Tenancy concept
• Exposure to Cloud Services, Cloud Storage, Compute Services, Application Services
• Exposure to MLOps, LLMOps
• EIA, Performance Tuning, Cost Optimization (FinOps), CBA
• RAI practice
• Relevant Certifications
• Domain Skills (in any of the below sectors):

Banking: 

• Retail/Consumer/personal Banking, Commercial/Corporate Banking, Investment Banking
• Regulation and Compliance
• Relevant Certifications
   

Insurance:

• Insurance domain (KYC, Onboarding, Policy, Plans, Premium, Payments, Renewal, Claim)
• Regulation and Compliance
• Relevant Certifications
   

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