Muhammad Ahsan

For one of the largest telecommunication-based clients, I am hands-on involved in designing an event-driven architecture of a deep-learning (CNN) powered product. Leading the implementation and MLOps of multilabel image and video classification. Implementation of CI/CD for the microservices and ML pipelines on GCP. Releasing data science artifacts using BigQuery and GraphQL-based microservices. Setting standards for production-ready ML codebase and best practices.

I was responsible for designing resilient and scalable architectures of multiple machine-learning systems. Implementation of ml-pipelines for model training, evaluation, deployment, and monitoring. Leading the backend development of a machine-learning-based recommendation service. Monolith system migration to asynchronous micro-services using strangler patterns. Supporting stakeholders in the further development of machine learning and data solutions.

I was responsible for providing technical leadership and helping the management with the data strategy. Defining the vision, and goals including outlining the roadmap of the data science team. Architect, implement and roll out pricing-focused products driven by machine learning. Taking ownership of existing non-operational data science artifacts and operationalizing them through microservice architecture. Supervise the development of ML pipelines for training, evaluation, deployment, and monitoring.

Worked in big data analytics to extract marketing intelligence insights. Performed quantitative analysis, pattern mining and statistical modeling to understand how we drive value for our clients. Involved in complete data science life-cycle right from business and data understanding up to modeling, evaluation and deployment. Reported, visualised and communicated results to internal and external stakeholders.

I was responsible for exploiting machine learning algorithms for team formation in a new scientific research lab. It included generating large snapshots of co-authorship networks using scientific publications. Feature engineering, training, evaluation, and hyperparameter tunning of models. Finally, within the hiring budget and scientist's productivity predictions, forming teams that would maximize the likelihood of overall future productivity.

I was responsible for database programming using Java, SQL, Oracle PL/SQL, and UNIX scripting. Database performance and query optimizations. Data analysis of financial and non-financial transactions. Designing data migration strategies and ETL pipelines. System bug simulation, and troubleshooting. I was also part of the technical support team (T2/L2) in three-tiered support architecture. I also managed technical and business communications simultaneously between the client and vendor.

I was responsible for the execution of practical lab sessions as part of computer science courses. Leading technical lab sessions including evaluation of undergraduate students. Programming lab sessions in C/C++, Java, and Database Management Systems. Providing teaching support to senior faculty for the ongoing undergraduate courses in the computer science department.

Specialization in Relational Pattern Mining