Lead Consultant/Data Scientist
ALLSTATE
Total years of experience :14 years, 2 Months
Lead data scientist
Lead data scientist
Key Result Areas:
•Worked on SAS, SQL SERVER, R, RAPID MINER and WEKA for the Month End Automotive Sales forecasting Projects.
•Visualisation using EXCEL and SSRS for the Month End forecasted results.
•Exploratory Data Analysis, Generating Summarized Univariate and Bivariate Analysis reports for Month End Forecasting Project and Customer Loyalty Analytics Projects.
•Conducted Knowledge sharing sessions on VARMAX forecasting procedure using SAS and R, PYTHON for data Analysis, RATTLE for Data Mining
•Communicated effectively with the client in understanding and solving the business problems
•Worked on Univariate Time Series forecasting projects.
•Worked on Classification algorithm (Naïve Bayes’, Logistic Regression for the Customer Loyalty Analytics projects.
•Worked on Decision tree, Random Forests and Neural Network algorithm for the Customer Loyalty Analytics Projects.
•Worked on Regression Analysis (OLS, Ridge) to find out the most important factors that influences customers purchase decisions in an Automotive Industry
Key Result Areas:
•Worked on SAS, SQL SERVER, R, MINITAB for Pharma analytics Projects
•Dashboard preparation for pharmaceutical products performance and processes, adhoc sales Analysis
•Data analysis using SAS, R, Advanced excel and SQL. Generating product performance reports and delivering it to the client.
•Worked on sales representatives profiling/segmentation using Clustering/Decision Tree, Random forests in R, SAS E Miner
•Understand, deliver and automate daily, weekly & monthly reporting of business performance.
•Build a monthly dashboard (aggregate of existing reports) to summarize the overall business performance.
•Provide insightful updates for business.
•Ad-hoc data analysis for day-to-day running of business.
•Extracting and manipulating data as well as producing suitable output/presentations including reports and charts.
•Forecasting of the Pharmaceutical Product sales using ARIMA, VARMAX, and Simple moving average
Key Result Areas:
•Worked on SAS, R, SQL SERVER, Logistic Regression, Naïve Bayes classifiers, Decision Tree for the Banking Analytics project.
•Applications of linear and logistic regression in banking sector for Collection strategies/ Scorecard development.
•Involved in various projects. Preparing Data quality and data integrity reports on the data.
Implementing analysis linear and logistic regression analysis
Key Result Areas:
•Identifying the key clinical information to be recorded in NextGen from the source document. (Worked with different modules- Medication, Allergy, Past Medical History, Chronic problems, Lab modules, etc.)
•Direct client communication, which involved training and demonstration of EHR and other in- house software to the clients, understanding the client requirements and making proper documentation for the modifications in software, template modification & customization.
•Worked on Clustering/Segmentation in R to group the patients on similar medical patterns.
•Developed high-end visualisation using SSRS for the length of stay of patients in the hospitals.
•Electronic Health Record Management.
•Worked for a multi-specialty hospital (more than 40 hospitals in the group) in managing their Electronic Health Records
•Managing clinical query management process with onsite RN & doctors.
•Implementing new guidelines and updates in day to day workflow
•Project Tool:
•NextGen
•R/SQL SERVER
Key Result Areas:
•Dealt with the medications and have immense knowledge of it.
•Served as the first line resource for Clinical Customer Issues with apt resolution instructions and escalating the same to the physicians for the Medicare Part D drug plan.
•Worked on Segmentation/ Clustering in R to identify the factors for the fraudulent claims.
•Accountable for Claims Analytics. Worked on Classification techniques like Logistic, Naïve Bayes to identify/ predict the fraudulent claims.
•Coordinating with in house physicians for understanding impact of application configurations for meeting customer goals and expectations.
•Associated with Drug Utilization Management.
•Pharmacy and Therapeutic Committee decisions and review.
•Involved in the drug prior authorisations.
•Significant Highlights:
•Participated in the training of Medication Therapy Management.
•Involved in the claims analytics process.
•Provided health solutions to 20 U.S state beneficiaries on their Medicare Part D Drug plan.
Significant Highlights:
•Participated in the training of Medication Therapy Management, R, Citrix, Cognos, CMS, HIPAA, PDP and Procare
•Involved in the health insurance claims analytics process.
•Provided health solutions to 20 U.S state beneficiaries on their Medicare Part D Drug plan.
•Trained new joinees on "Pharmacy Benefit Manager (PBM) and R “software operation
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Six Sigma LEAN Trained, Tested and Certified from Genpact •Six Sigma Green Belt Trained •Online Computing for Data Analysis using R from Coursera •MINITAB Quality training from MINITAB •Data Mining with WEKA
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