STS Welcomes Subhasis Datta, Data Science Principal
Simple Technology Solutions (STS) is pleased to announce and welcome Subhasis Datta, Data Science Principal.
Subhasis joins STS with over 25 years of experience as a Chief Data Scientist, Chief Systems & Software Engineer/Architect, VP & Technical Director, Program/Project Management, Machine Learning(ML)/AI Expert and Practice Lead. He led successful design, model building, test and validation, real-time deployment, and performance analytics at over five dozen ML/AI, enterprise-wide data analytics programs across multiple Federal Agencies, the DoD and a number of intel agencies.
At STS, Subhasis will be responsible for organization-wide building and oversight over all Data Science, ML/AI enterprise-wide programs across DHS (TSA, USCIS, CBP, etc.), HHS, other Federal Agencies, DoD and its components, Intel agencies etc. Subhasis will be responsible for recruiting, building and mentoring a world-class Data Science, ML/AI team supporting all STS agencies and programs. Subhasis will be responsible for significant growth of STS as a lead proposal author, thought leader, and ML/AI SME.
Prior to joining our team, Subhasis was the Chief Data Scientist, Director of Machine Learning and Artificial Intelligence at Analytica, LLC, where he supported multiple analytical programs at the SEC, DHS and Health and Human Services. As the Technical Program Manager and Chief Data Scientist at SES Corporation, Subhasis led the largest Integration, cloud engineering and analytics program at The United States Census Bureau.
As Chief Data Scientist, Technical Director, and Program Manager at ICF International, Subhasis transformed one of the largest Federal IT Infrastructure outsourcing programs valued at over $1.5B while maintaining a Data Scientist Advisory role at the USPS, DHS, State Department, FDIC, PBGC, etc.
Another dual role as Chief Data Scientist/Architect and Director of Systems & Software Engineering, Subhasis led a portfolio of Analytical, Machine Learning (ML) and AI, Infrastructure and Systems Engineering, and Enterprise Architecture programs at the MITRE Corporation. A thought leader transformed Chief Data Scientist, he led multiple Fraud Detection, Compliance Improvement, Modeling and Simulation and Analytics programs. During his time at MITRE, Subhasis managed one of the world’s largest ‘Big Data’ fraud detection systems while increasing revenue protection by 2,500%.
Subhasis spent 10 years as the Assistant VP, Director for the Center for Data Science and Systems Engineering and Chief Data Scientist at Alion Science & Technology. built and led a Practice in Data Science, ML/AI with a team of over 25 Data Scientists/Engineers, Systems and Software Engineers. There, he led large analytics and engineering teams through customized software development programs at Federal Agencies and DoD services including Air Force Predictive Readiness Assessment System. Additionally, he led several Corporate Software company acquisitions, COTS software development in Transportation Modeling, Simulation and Logistics Optimization, Security and Vulnerability Assessment, and Incident and Command Management.
Subhasis holds graduate degrees and doctoral work in Analytics, Data Engineering, and Operations Research/ Management Science. He is currently completing his MS in Systems Engineering at Johns Hopkins. Subhasis is a Professional Alumni at the Massachusetts Institute of Technology after completing courses in Big Data Analytics, IoT, and ML/AI. He has completed multiple Key Data Science ML/AI, Big Data, Cloud, Open Source languages and ML algorithms courses, Deep Learning at Stanford. Subhasis holds a BS in Engineering, an MS in Information Systems and Management Science, and an MBA from the University of Maryland, College Park.
Certifications: Data Science, ML/AI, ITIL and Knowledge Management.
Volunteerism: NIST Standards group in Big Data, Industry leading body ACT-IAC, Statistics and Data Without Borders to support United Nations, UNHCR, NGOs.Member: MIT Alumni Association, IEEE, ACM, SIGKDD, INCOSE, Big Data & Data Science Association and Data Central Organizations.