Aditi Bohra

Secure a responsible career opportunity to enhance my experience and skills in the field of Data Science, while making a significant contribution to the company. Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in [Area of expertise].

• Forecast the impact of COVID on diabetic market for different countries: Forecasted the impact of COVID on sales on diabetic market, using the secondary desk research and IQVIA sales data helped in predict direct or indirect impact on the sale during the pandemic as the countries were shutdown, finding the trend and reason for the decline and look at the percentage of stock pilling before or during pandemic.
• Market Mix Modelling or Promo Mix Model: Market Mix Model is the predictive model which help client to understand ROI (returnof investment) of each investment done on the multiple promotions which increase the sales,And recommend the channel to invest to increase the sales.
• Reduce the OPD visits for Respiratory Tract Infection: To design pattern of rules and patient segment that help us to determine the need of OPD visits for upper and lower respiratory tract infection,so that insurance company can give a tele consultation to counsel and suggest symptomatic treatment as necessary.
• Comparing the treatment between Dulaglutide and Liraglutide Compared adherence, persistence and describe the treatment patterns over 12 months post index period between Dulaglutide and Liraglutide, before and after adjusting for confounders for Type 2 Diabetic patients Techniques: Propensity Model, MC-Nemar test, Chi square test, paired and unpaired t test
• Trail Cost Projection Solution: Built a Trial Cost Projection Solution that aims to provide business users with an ML based solution to estimate clinical trial costs. the solution Identifies the important drivers of costs and transform the cost drivers into features to feed into the model and using the cost drivers to build the total cost model.