Skilled in data cleaning, manipulation, and visualization. Experienced in building dashboards using Alteryx, Tableau, and Power BI. Have an in-depth understanding of the pharmaceutical industry and drug commercialization.
Industry and Project Experience
⦿ Developed an in-depth understanding of the pharmaceutical industry including sales measurement, field force, field force activities, managed care, deciding and targeting.
⦿ Performed extensive analysis using SAS/SQL on pharmaceutical datasets such as Xponent, DDD, Roster, Alignment, Xponent Plantrak, Master Profile, Calls, and Samples datasets.
⦿ Conducted market analysis on branded drugs using SWOT model by analyzing prescribing information, mechanism of action, clinical trials, acne treatment options, major competitors, and marketing strategies.
⦿ Analyzed how patients respond to XIFAXAN over time and conducted the duration of treatment analysis using APLD data.
⦿ Support Novartis US Breast Cancer Commercial Analytics team:
o Assisted in the development of data automation codes to generate weekly and monthly brand performance reports utilizing Xponent, SP and APLD datasets in Python.
o Prepared and updated weekly brand performance presentation slides for drugs.
o Conducted EDA independently of IQVIA’s longitudinal health plan database PharMetrics Plus on Snowflake.
o Separated and generated tidy diagnosis, procedure and prescription datasets from the claims dataset which had over 13 billion records.
o Identified breast cancer-related diagnosis codes and secondary malignant neoplasm-related diagnosis codes from 98k ICD codes, breast cancer-related surgery and radiation therapy codes from 71k CPT codes.
o Established business rules to categorize early breast cancer and metastatic breast cancer patients based on the thorough study of 300+ different types of patient journeys and 200+ types of drug use journeys.
o Studied and visualized market share, total new patients, and total prescription trends over time for different types of breast cancer drugs.
o Analyzed the reasons behind the increasing sales of our main competitor’s product.
o Built decision tree and clustering models to distinguish early breast cancer and metastatic breast cancer patients.