Deputy Manager - Technical Lead Data Science Nissan ISIT

Tech Lead leads the planning, execution, and delivery of AI/ML programs across the organization. This role requires a strong blend of technical expertise (ML, DL, Generative AI, Computer Vision/OpenCV) and program management capabilities to drive scalable, high‑impact AI initiatives. The individual will work closely with data scientists, ML engineers, software teams, and business units to transform AI strategies into production-grade solutions

Program Management

 Lead multiple AI/ML projects from concept to deployment by defining scope, timelines, deliverables, and KPIs.

 Develop AI roadmaps aligned with business goals and strategic outcomes.

 Ensure smooth cross-functional collaboration between data science, engineering, product, IT, and business teams.

 Drive Agile/Scrum ceremonies for AI teams—backlog grooming, sprint planning, retrospectives.

 Manage risks, dependencies, and resource allocation across AI portfolios.

Technical Leadership

 Lead the design and implementation of GenAI-powered applications like chatbots, copilots, document intelligence, synthetic data, and automation.

 Drive enterprise adoption of LLMs and multimodal AI systems.

 Manage experimentation, PoCs, and pilot deployments of GenAI solutions.

 Provide technical guidance on ML/DL model selection, evaluation, data requirements, and deployment strategy.

 Review architectures involving CNNs, RNNs, Transformers, autoencoders, and custom vision models.

 Oversee Computer Vision Initiatives Using OpenCV

• Image classification, object detection, segmentation
• OCR and document analysis
  
  

• Strong understanding of Machine Learning, Deep Learning, NLP, Generative AI, and Computer Vision.
• Hands-on familiarity with:
• Python, TensorFlow, PyTorch
• OpenCV, YOLO, Vision Transformers
• LLMs, prompt engineering, vector databases (FAISS, Pinecone)
• MLOps tools (MLflow, Kubeflow, ML, AWS Sagemaker)
• Data engineering concepts (ETL, pipelines, APIs)
  

• Experience with Agile/Scrum methodologies.
• Strong documentation and communication capabilities.
• Ability to balance technical depth with strategic business understanding.
• Experience managing large-scale, cross-functional projects.