Akshay Mankar

Data Scientist and Machine Learning Engineer with 9+ years of experience building end-to-end AI systems across manufacturing, automotive, and industrial domains. Currently leading a team of Data Scientists at SABIC, developing predictive material behavior pipelines and organization-wide data governance frameworks. Proven track record spanning the full ML lifecycle — from translating ambiguous business problems into technical solutions, to deploying production-grade computer vision and NLP systems. Core strengths include Computer Vision (YOLO-based defect detection, image classification, segmentation), sensor and time-series data analysis, and applied NLP/LLM systems (RAG, vector databases, LLM fine-tuning, named-entity recognition). Delivered measurable business impact, including automated aero-engine defect localization to reduce maintenance downtime, faulty fuel-injector inspection systems that got integrated into design QA processes, and predictive maintenance analytics for automotive fleets. Experienced leading cross-functional and distributed teams — from bridging BMW and Arriver engineering groups on autonomous driving (ADAS) projects in Germany, to heading analytics teams for Volvo Trucks in Sweden, to my current data science team in India. Comfortable owning projects from stakeholder scoping through model development to MLOps deployment (Docker, MLFlow, Vertex AI, Microsoft Fabric). Technical toolkit: Python, SQL, TensorFlow, Keras, Scikit-Learn, LangChain, Hugging Face, OpenCV, Power BI, Streamlit. Currently open to remote, contract, or consulting-style roles with international teams — particularly in applied AI/ML, computer vision, or data science leadership — where I can bring hands-on technical depth combined with experience managing distributed, cross-cultural engineering teams. Comfortable working async across time zones, having done so previously with teams in Germany and Sweden.