Mohammad Laeeq Siddique

Data Science, Statistical Machine Learning and Big Biology enthusiastic. Academic background rooted in Data Engineering, Statistics, Computational Mathematics, Machine Learning, Bioinformatics, Systems and Integrated Biology with 10 years of Industry experience in organising, analysing and monetising information assets. Strong Understanding of genomics, proteomics Technologies and data analysis methodologies. I focus on successful translation of user needs to develop strategy for user centred design, leveraging standards, best practices, task analysis, stakeholders input and iterative modeling and usability testing. I am responsible for building and maintaining our Taxonomies and Ontologies, internal metadata models and classification schemas for content enrichment. For the past 10 years I have been working with data procurement,hypothesis generation, hypothesis scoring, classification systems, ontologies, controlled vocabularies, taxonomies and search engines helping improve the find-ability and usability of information in life science & Healthcare, Banking, Retail and HighTech Space. Particular expertise in Machine learning, Data mining, Cognitive Computing, Natural Language Processing, Image/Video Processing, Taxonomies, Ontologies, Controlled Vocabularies, Semantic Text mining, media monitoring, Thesaurus, Metadata, and content classification and content tagging Vector Space and Graphical data mining Graph and Sequence data mining Signal Processing [Genomic Signal Processing] Genomics and Molecular Diagnostics Drug Discovery and Drug Design using machine learning Techniques Statistical Analysis tools like R, Matlab and Python