Senior Data Scientist SME & AI

🌟 Senior Data Scientist SME & AI Architect (10+ Years Experience) 🧠

We are seeking a highly accomplished and results-oriented Senior Data Scientist Subject Matter Expert (SME) with over 10 years of experience to lead our advanced analytics and AI initiatives. This is a pivotal role requiring deep technical mastery across large-scale Big Data technologies, multi-cloud environments, and cutting-edge specialized AI domains, including Generative AI, Computer Vision, and Natural Language Processing (NLP) .

You will be the principal technical leader, driving strategy, setting standards, and delivering high-impact solutions that transform business outcomes.

Key Responsibilities

• AI / ML Strategy & Architecture : Define the technical roadmap and architectural standards for deploying and scaling complex AI systems, particularly those involving Generative AI (GenAI) , large language models ( LLMs ), and specialized models in Computer Vision and NLP.
• Big Data Engineering : Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference.
• Cross-Cloud Execution : Lead the design and deployment of ML models and data infrastructure across multiple major cloud providers ( AWS, Azure, and GCP ), ensuring portability, scalability, and cost efficiency.
• Specialized Model Development : Lead hands-on development, fine-tuning, and deployment of production-grade models in key specialized areas :
• Computer Vision : Developing and optimizing models for image recognition, object detection, and video analytics.
• NLP : Building sophisticated systems for sentiment analysis, entity extraction, semantic search, and RAG architectures leveraging LLMs.
• Generative AI : Exploring and implementing cutting-edge GenAI techniques for content creation, data augmentation, and innovative product features.
• SME Consulting & Mentorship : Act as the internal authority and consultant, providing technical guidance, architectural review, and mentorship to junior data scientists and engineering teams.
• MLOps & Governance : Establish best practices for MLOps, model monitoring, version control, and model risk governance in a multi-cloud production environment.

Required Skills and Expertise (10+ Years)

1. Big Data and Cloud Mastery

2. Advanced AI / ML Specialization

3. Leadership & Soft Skills

Education and Certification