Regulatory Submissions helper: Led the development of a Retrieval-Augmented Generation (RAG) application for regulatory product submissions and question answering, streamlining regulatory approval processes for a medical device manufacturer.Semantic Search Integration: Implemented Generative AI solution for semantic search in scientific research databases, utilizing zero-shot Named Entity Recognition (NER) via Large Language Models (LLMs) on Azure Search's Vector Database.AI-Driven Service Desk: Developed an AI-driven troubleshooting system using RAG agents to automate problem resolution steps and optimize knowledge base searches, employing advanced document processing and text segmentation to keep the context intact.

MLOps Enablement: Led an MLOps project for a major bank, educating teams and implementing end-to-end pipelines on GCP Vertex AI and BigQuery for ETL, model training, deployment, and monitoring.Heart Failure NER Engine: Developed a rule-based NER matching engine using spaCy on patient health records to predict additional care requirements for heart failure patients.Team Upskilling and Project Management: Advanced team proficiency in AI/ML through upskilling programs; managed project timelines to ensure on-time, on-budget delivery of complex ML projects.

Fire Prevention Analysis: Applied Extreme Value Analysis to sensor data from mobile mining equipment to predict fire hazard conditions and flag maintenance.Customer Data Unification: Built a Unified Customer Database (UCD) ML pipeline processing over 1 billion orders one time load and few million orders every day, predicting matching groups. Deployed via a fully automated MLOps pipeline.

- EDT (Estimated Delivery Time): Engineered a predictive analytics framework utilising both internal metrics and external data points for forecasting order readiness and delivery timelines. Implemented a fully automated MLOps training and model promotion pipeline on KubeFlow, deployed on AWS, enabling real-time predictions via AWS Lambda behind an API Gateway. Operational across 9 countries in 3 regions (EU, ANZ, JP).- FOS (Future Order Screen): Developed a predictive model to analyse web interactions on the ordering platform, identifying potential orders before payment confirmation. This predictive insight accelerates the preparation process, enhancing delivery efficiency and product freshness. Employed a reusable MLOps pattern for model training and deployment, akin to EDT, facilitating real-time predictions through AWS Lambda integrated with an API Gateway. Deployed across 7 countries across EU, ANZ, JP.- UCD (Unified Customer Database): Orchestrated a comprehensive integration of customer data (approx. 1 billion online orders), optimising for analytical processing and targeted marketing campaigns. Applied advanced data engineering strategies and domain expertise to minimise computational demands, enabling full-scale processing on a single VM. Deployed via a fully automated MLOps pipeline, active in 9 countries across EU, ANZ, JP.- Rostering & Forecasting Platform: Implemented a forecasting model to predict various sales metrics and order types two weeks ahead at 15-minute intervals, supporting strategic staff scheduling in retail environments. Harnessed cutting-edge feature engineering to capture essential forecasting signals, using a scalable MLOps framework for model training and deployment. Available in 7 countries across EU, ANZ, JP.

Data Science & AI consultancy role with projects in big data. - Constraint optimisation project with focus on building big data pipelines using SQL, Informatica PowerCenter, Azure HDInsight Hive Data Lake. - Optimisation model using location data and business specific constraints. - Actionable insights with model output in form of PowerBI dashboards.

Applied Machine Learning role with key focus on automating real estate management solutions with the help of machine learning.Lead various projects from data collection, annotation to production system deployment with special attention to real-time results.• Developing machine learning and artificial intelligence solutions to various business problems related to real estate market.• Building and maintaining complete deployment pipelines from data collection to training the machine learning models and serving APIs in production scale using CI/CD.• Following ETL (Extract, Transform, and Load) process for data input and manipulation using SQL queries, numpy, pandas and TensorFlow dataset API.• Data Engineering / Feature Engineering to obtain meaningful information from existing data.• Data augmentation to increase the amount of training data and improve model performance.• Building machine learning models to solve computer vision, NLP (Natural Language Processing), regression, classification and clustering problems using Python and TensorFlow.• Serving machine learning models by building custom APIs using Django, Flask or Tornado web frameworks or using TensorFlow serving in Docker containers on Azure App Services.

Using Adobe Illustrator, Photoshop, Sketch and Figma to design UI/UX for real estate management suite of products. This included revamping the designs of multiple web apps and mobile apps as well as designing new web and mobile apps from scratch.

Defined go-to-market strategy for Cielo WiGle Smart Home Products.Defined core user experience features for Cielo WiGle Smart Home Products.Champion and propose new features that help make user experience for a Smart Home Product easier and simpler.Champion and propose innovative features for smart home products that should help stand-out in the market.Own product requirements definition (including writing requirement documents and user stories) of new product features and enhancements.Drive definition, requirements, design, functionality and performance working with various stakeholder.sCreate and maintain a roadmap for Cielo WiGle Smart Homes product family and a pipeline of features.Work closely with development team to ensure implementation of market needs.

Managing and providing leadership to the project team.Effectively executing the role of lead field representative of the company in various interactions with customers.Responsible for identification and compliance of contractual requirements.Coordinating system technical design and components specification for PV systems with engineering department.Oversee mobilization and installation plans and coordinate installation activities with project team.Reviewing project cost reporting, invoicing, and accounting with Finance Manager.Overseeing development of safety, quality control, testing and system commissioning plans.Overseeing completion of utility interconnection agreements, rebate applications, and inspections.Overseeing preparation of manuals, drawings, reports and other documentation.Providing and overseeing customer training.Coordinating maintenance planning and handing off of post-installation support to Customer Service.Tracking and monitoring sales performance of Distributors in two districts.

Organizational Based Learning in Sales and CSR ProductionPartner in the Sales team.Generating sales leads.Working with Product Development Department for Sample development.Negotiation with client in order to approve developed samples.Conducting order processing activities.Keeping clients in-line till complete order processing.Making preparations for CSR audit for production department in order to secure supplier license.Assisting external Audit team in successfully conducting the CSR audit.