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henrico,
united states
Datum, tid och plats: 11:43 em
Gick med mars 30, 2018
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Subhash J.
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henrico,
united states
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Återanställningsgrad
An experienced and inquisitive Data Science team
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Erfarenhet
Data Scientist – Research
aug. 2016 - Nuvarande
Turned the algorithm output of natural language sentence filters into a shiny app where transplant centers could edit the algorithm generated filter.This would allow the transplant center to be more or less risk-averse than the automatic filter creator. Answering ad hoc data requests (in R/SAS/SQL/Tableau) to help make better use of the match data Working on supporting a 3-cluster R Server with 15-20 users at any time doing knitting, statistics, manipulations, analysis, and publishing documents
Owner
juni 2011 - Nuvarande
Building out data products for internal tools or external enhancements for customers from idea to production
Delivering ETL solutions for external and internal data sources
Upgraded optimization software for targetted networking events
Helped implement Tableau Server into a client’s ecosystem with suggestions and ad hoc reports
Created an algorithm to predict the potential cyber security threat against a given company
Data Scientist-Consumer Insights Team
dec. 2015 - juli 2016 (7 månader, 1 dag)
Alteryx to automate workflows.Tableau to present,ShinyR to deploy applications.Tapped into macro/ micro open data sources to increase the predictability.Used predictive methods to enhance the cluster analyses done previously, showed it simply via Tableau. Used text mining algorithms on untapped transactional and longitudinal data to bring new insights. constructing complex statistical models/ machine learning algorithms to fit the problem/ packaging them into data products, based in ShinyR.
Utbildning
Master of Science - Decision Analytics
(1 år)
Bachelor’s Degree - IT Management
(3 år)
Kvalifikationer
Forecasting Model
Luckstone (Luck Company)
2017
Worked on munging data from FRED and BSEE to predict their sales/stone usage. In R, I did the data cleaning, pulling out from sources, coding the correlations, and using samples to determine if our model was valid. Forecasted MAPE of 3.4% led to a potential of $1.6 million waste reduction
Sentiment Analysis
Analytic Adventures
2017
Built a tool that helped Southern States do sentiment analysis to better understand what/how their customers were feeling based on the AFINN Index and a customer library of string to sentiment. It was programmed in R and integrated with Alteryx
Zero Risk Credit Approval
Capital One
2017
Built a web-based statistical model to match those who are looking for houses with those who have houses for people to rent. Craigslist was scraped with python and stored with SQLite. R then took care of the sentiment analysis and natural language features to process and finally match the two (tenant and landlord).
‘Zero’ Risk Credit Approval
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