Chief Data Scientist
Ajish is a self-avowed data-nerd and polyglot polymath with a passion for building scalable data products from scratch, and a deep background in analytics/ML, back-end/big-data engineering, front-end/mobile development, and devops/cloud architecture. He started college at age 16, graduated from RPI with a BS at 19, then went on to found biotech startup Hocus Locus and complete his PhD by age 24. Though formally trained in genomic biology, particularly the analysis of high-throughput genome sequencing data (with 22 published papers, 6 patents, and one startup founded and funded in the field), he branched out into the ad-tech space, holding senior positions in NYC’s Silicon Alley Lumascape, and into the consulting racket, working as advisor, engineer, and scientist for early to mid-stage startups, academic concerns, and larger corporations looking to join the big-data party. He is a former political pollster, EMT, and zombie zebrafish farmer, with stats and ML expertise in topics including supervised and unsupervised classification, PGMs, HMMs, MCMC, and other Bayesian methods, survey statistics, network theory, neural nets, regression and time-series analyses, natural language processing, ontology and topic modeling, recommender systems, and applied TANSTAAFL/Free-Lunch theory.
Ajish is comfortable architecting systems from backend to front-end, utilizing high-performance APIs and microservices, deploying best-of-breed cloud services and distributed data platforms, developing ELT and real-time analytic workflows with the latest big data stacks (Hadoop, Spark, NiFi, Arrow), leveraging statistical and machine-learning libraries, or composing slick front-ends for web or mobile. He has worked with and managed teams of engineers, analysts, marketers, and researchers to create novel data products with scalable architectures, cutting edge analytic components, and bespoke visualisation and management interfaces, and thrives on deep dives into complex problems that require both creative and analytical thinking, and a knack for research, experimentation, and empirical validation.
Ajish is a member of various professional organizations including the American Statistical Association (PStat) and Association for Computing Machinery (ACM, SIGMOD), and while not herding data unicorns or catching frogs in the big-data swamp, he teaches courses in data science, genomics, and related topics as an Adjunct Professor of Data Analytics at the University of Maryland University College.
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Specializing in the design and development of software systems for the health and life sciences industries
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