Senior Data Scientist

# ; 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 Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark , with strong preference for production development using Scala . Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated expertise in deploying and managing data/ML workloads across at least two of the three major cloud platforms: AWS (Sagemaker, EMR, S3), Azure (Azure ML, Synapse Analytics), and GCP (Vertex AI, BigQuery). Data Architecture: Expert knowledge of distributed systems, data partitioning, optimization techniques, and data warehousing concepts in a cloud-native context. 2. Advanced AI/ML Specialization Generative AI (GenAI) & LLMs: Proven experience with the architecture and implementation of Generative AI solutions, including prompt engineering, fine-tuning, and deploying Large Language Models (LLMs) . Computer Vision: In-depth knowledge of deep learning frameworks (TensorFlow, PyTorch) and experience with Computer Vision tasks (e.g., CNNs, object detection models like YOLO). NLP: Expert practical experience in NLP techniques, including transformer models, embedding generation, and building complex text-based applications. 3. Leadership & Soft Skills Technical Leadership: Proven track record of leading complex data science projects from research to production deployment. Communication: Exceptional ability to translate complex technical findings into clear, strategic recommendations for technical and executive audiences. Mentorship: Experience mentoring and training senior engineers and data scientists. Education and Certification Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a highly quantitative field. Relevant professional cloud certifications (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Data Engineer) are highly desirable.