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Senior Sas Analyst Resume

Horsham, PA


  • Have 11+ years of Sales and Marketing business analytics experience in life sciences & healthcare, expertise in engaging clients and leading teams.
  • Proficient in supervised and unsupervised machine learning techniques. Completed Master’s in Statistics, sound knowledge in analytical techniques.
  • Independently handled Data Sciences teams, Oncology Brand Analytics, Seroquel, and Crestor Brands, Diabetes and Cardiovascular Brand reports and Erivedge Brand teams.
  • Worked in Marketing Science, Field Sales Analytics, Commercial channel operations, Brand Analytics, Managed Market Insights and Bio Oncology projects.
  • Involved in Segmentation, Sales force restructuring effectiveness, Return on Investment Test Control Analysis, sample allocation projects and developed analytical reports for Forecasting and IC teams.
  • Quantitative Analytics, Statistical Applications and Big Data Management using SAS (UNIX/Windows), Enterprise Guide, SQL, SAS Studio and SPSS analytical software’s.
  • Multivariate/ML techniques - Multiple Linear Regression, Decision tree analysis, Principle component analysis, CHAID, Discriminant analysis, Factor Analysis, Random Forests, Cluster Analysis, etc.
  • Practical QlikView and Complete QlikView Boot Camp programs - through Udemy
  • Independently handled SAS Big Data Management production process.
  • Supervised Machine Learning algorithm - Decision Tree Analysis developed to determine optimum cut-off prescription level for psych brand and its competitors, Derived SOB metrics, Promotional analysis, etc.
  • Unsupervised Machine Learning algorithm - Cluster Analysis is developed to segment physicians in to various categories to perform sales promotions and sales targeting.
  • Supervised ML - CART - Discriminant analysis is performed to classify existing credit card bank customers in to Platinum, Gold & Silver, use the model to identify new customer’s eligibility and determine which type of cards suits.
  • Supervised ML- Multiple Regression Model is developed to identify Leads and Enrollments.
  • Naïve Base - Conditional probability model is developed to identify student’s retention rate.
  • Developed Multiple Regression Machine Learning model - to identify Rx patterns - using parameters like market share, NRx and TRx shares, volume, details and samples. ATU market research reports - analysed persuasive trends.
  • Return on Investments, Profiling and Segmentation, Marketing Mix Models, Adherence and Persistency Models.
  • Managed and delivered large volume of Field Sales KPI reports - EBD CBL reports, Executive Suite of Reports, DSM Coaching Days report, Hospital reports, etc.
  • Managed SAS datasets through ETL process, involved in data cleansing, Quality Checks, developing SAS codes, process automation, enhancements, performance tuning, optimization, error handling, file transfers, etc.
  • Developed analytical models to identify customer retention rate, Lift Time Value and attrition/churn patterns
  • Developed SAS programs to derive extracts using SQL BI Query tool, ORACLE TOAD.


  • Machine Learning
  • Quantitative Insights
  • SAS Certified
  • Analytical Reporting
  • QlikView/Tableau
  • Data Analysis
  • Market Research
  • Statistical computing
  • SAS Data Management
  • Leadership Acumen


  • SAS 9.4(UNIX/Windows), SQL, Enterprise Guide, Enterprise Miner, JMP 9, SPSS and MS Access
  • QlikView, Tableau, Microsoft Office (Excel, VBA, PPT)
  • Proficient in Machine Learning, Multivariate Analysis, Data mining techniques including Predictive Analytics
  • Hands-on Python & R in Data Sciences - Deep Learning hands-on Artificial Neural Networks - ongoing courses


Confidential, Horsham, PA

Senior SAS Analyst


  • As a Senior Analyst, assigned in Oncology and Immunology data sciences unit, developed SAS programs to analyze Specialty Pharmacy Datasets, creating Patient Persistency and Adherence insights that helps forecasting team to make decision on sales month on month.
  • Developed Aligned and unaligned sales reports to compare existing allocation rules and identify accounts where there are missing sales and identify over allocated units for Incentive and Compensation team.
  • Integrated multiple vendor data files and developed Confidential.
  • Sub-national report dashboards, Line of Therapy, Average Daily Dose Analysis, Pills per Day report, handled ad-hoc requests and developed visual analytical reports.

Confidential, Wilmington, DE

Senior Associate


  • Interactive analytical reports are generated for Confidential ’s field sales force, Executive Business Leaders, Commercial Brand Directors and Pharmaceutical Sales Reps have direct access to the reports in order to see sales performance on respective RDT’s and make decisions.
  • Dashboard KPI Reports are prepared for all brands includes Primary care, Executive Suite of Reports, CV Specialty, EBD-CBL reports, Hospital reports, DSM coaching days, CNS Seroquel, etc. Metrics includes recent trends on NRx, TRx, NBRx, Samples & Executions at District, Region and National levels
  • Quantitative decision support is provided based on business requirements. Involved in projects like identifying Part D - Low Income Subsidy groups, finding affiliations between Confidential and HCA, Statin Market analysis, developing e-sample analytical reports, Speaker program analysis on finding impacts of pre-and post-periods, APLD analysis reports, CSA Reports, Epanova Patient flow analysis, Sample Comparison Reports, Physicians individual blocking analysis, etc.
  • Project involves in conducting analysis at different levels of Confidential ’s Managed Market areas like Medicare, Medicaid, Part-D, Commercial, etc.
  • Developed analytical projects like Integrated Delivery Network (IDN) Reports, Brand Opportunity Analytical Reporting Tools for Brilinta, CV Specialty, 3A 3B Marketing Reports, Advocate reporting, Pharmacy level reports, Payer Potential Reports, Individual Ad-hoc level analysis for independent IDNs, Baseline Analysis, FFS Medicaid, etc.
  • All Payer Claims data - Health Plan Services extracts - Eligibility, Medical Rx claims, Mental Health, Provider data, foreign claims extracts. State Level APCD deliverables, ICD 9 to ICD 10 implementation. Prepared SAS extracts by developing SAS codes, extract queries from SQL BI query tool, perform quality control checks, developing and documenting SAS business process flows, analytical reports, UAT plans, FTP’s, cleansing SAS processes, etc.
  • Project activities involved to conduct Decision Tree Analysis to determine optimum cut-off prescription level for Seroquel and its competitors using EM, Derived SOB metrics calculation using APLD data.
  • Consumer Rebates Analysis - to assess the performance of Seroquel and Symbicort rebates programs. PROMO analysis - trends are observed on Details and Samples datasets of Seroquel, Nexium and Vimovo brands. Determine physician segments based on plan track, Rx, co-pay, PDE, etc. parameters, Model Seroquel XR’s Rx level using EM. ATU market research persuasive reports.
  • Raw data sets received from external vendors and teams like Corner Stone, IMS, McKesson, Dendrite, etc. will be processed via SAS jobs in UNIX environment. Need to develop SAS Codes according to client requirements, which include business level calculations, data transformations, etc.
  • SAS Data Mart - a complete production job setup implemented in UNIX environment, shell scripts are used to run these SAS codes on the backend on weekly and monthly basis.
  • Statistical techniques of CHAID, Discriminant analysis applied to identify the customer retention and attrition behaviours.
  • List of customers who are likely to leave from the account are identified and reported. Predictive model has been developed to identify whether a customer will fall under Platinum, Gold or Silver card based on the distinct customer end points.


Statistical Analyst


  • Regression analysis is used to forecast leads and enrolments of Confidential Students.
  • Amount spent through advertisements via various media’s along with macroeconomic indicators unemployment rates are used as parameters to predict & conditional probability approach for retention rate.


Statistics Lecturer and Project Co-ordinator


  • Apart from teaching regular statistical subjects, organized and conducted two tribal study surveys and a public opinion election survey, work involves in sampling, questionnaire preparation, analysis and reporting.
  • As a project coordinator, will guide/help students to identify their research areas, suggesting appropriate statistical techniques, conducting statistical analysis, preparation of reports & dissertations, etc.

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