At Analysis Group, I developed and implemented health economics and outcomes research strategies in a number of therapeutic areas including oncology, immunology, and infectious diseases. Specialized in the development and application of statistical research methods for health data, including electronic medical records and administrative claims. Designed and analyzed clinical trials, developed health economic models, investigated the impacts of formulary policy changes, built predictive models for health risks. At Columbia University, I worked on a wide array of projects sponsored by NIH developing models and analyzing data in public health and clinical sciences. At University of California, Berkeley, I developed models in time series analysis and point processes with applications in biological sciences Have taught courses in time series analysis, longitudinal data analysis, regression methods and introductory probability and statistics. Specialties: Time series Analysis, Longitudinal Data Analysis, Generalized Linear Models, Classification, R, Observational Studies

Senior Data Scientist @ Senior Data Scientist at Celmatix, a biotechnology startup that leverages innovations in data science, biology, and technology to help doctors and patients make confident, data-driven decisions about their fertility potential. For more information visit www.Celmatix.com From May 2015 to Present (6 months) Greater New York City AreaAdjunct Assistant Professor of Biostatistics @ I taught Longitudinal Data Analysis (Graduate) in the department of Biostatistics at Columbia University From January 2013 to May 2015 (2 years 5 months) Greater New York City AreaFellow @ Fellow in the third class of The Data Incubator (http://www.thedataincubator.com/), a highly selective (less than 4% acceptance rate) data science fellowship for PhD's in STEM fields. The Data Incubator is an intensive seven-week fellowship that prepares the best scientists and engineers with advanced degrees to work as data scientists. It identifies fellows who already have the 90% difficult-to-learn skills and equips them with the last 10%: the tools and technology stack that make them self-sufficient, productive contributors. Examples of projects I worked on include: • Manipulated data in Postgresql using Python psycopg2 and SQLAlchemy packages • Parsed web data to perform network analysis on social graph using python Beautifulsoup and Networkx packages • Performed various Machine Learning analysis using Python Scikit-learn and Pandas packages • Gained hands on experience running map-reduce jobs using Python package MRJobs • Performed Natural Language Processing (NLP) analysis using Python Scikit-learn, Pandas and Nltk packages - Gained hands on experience using Spark From February 2015 to March 2015 (2 months) Greater New York City AreaAssociate @ • Analysis of Randomized Clinical Trials (RCT) data • Treatment patterns analysis using large claims data • Experience working with claims data like MarketScan and OptumHealth • Statistical Analysis of data from FDA's FAERS/MedWatch data • Personalized medicine • Network Meta Analysis From January 2013 to January 2015 (2 years 1 month) Greater New York City AreaAssistant Professor of Biostatistics @ During my tenure at Columbia University, I worked on a wide array of collaborations as a Co-Inverstigator on projects funded by the the National Institutes of Health (NIH). Following is a brief list of representative projects: • Analyzed longitudinal data pertaining to Randomized Clinical Trials (RCT) from Alcohol addition trials • Developed time-to-event models with application to Obstetric Anesthesiology • Developed time series models for analysis of data from Cardiology • Analyzed data in neuro-anesthesiology using pattern recognition techniques • Developed dose-response models for studying the association between toxic exposures and cognitive and behavioral outcomes • Analyzed data pertaining to exposures and Asthma • Developed change point models to model RNA unwinding data I was also the instructor for the following courses: • Longitudinal Data Analysis (Graduate) • Time Series Analysis (Graduate) • Applied Regression (Graduate) From September 2008 to December 2012 (4 years 4 months) Greater New York City AreaSummer Intern @ - Developed Mixed-Effects models to analyze and compare DNA microarray data characterizing gene expressions of hepatic (liver) cells from rats subject to in-vivo and in-vitro exposure to various toxins. From June 2004 to August 2004 (3 months) Schenectady, NY

Doctor of Philosophy (Ph.D.), Biostatistics @ University of California, Berkeley From 2004 to 2008 Master of Arts (M.A.), Biostatistics @ University of California, Berkeley From 2002 to 2004 Master of Science (M.S.), Mechanical Engineering @ University of Missouri-Rolla Srikesh Arunajadai is skilled in: Statistics, Statistical Modeling, Biostatistics, R, SAS, Python, Machine Learning, Pattern Recognition, Time Series Analysis, Consulting, Big Data