Ever learning analyst keen on using data science to solve marketing & customer analytics problems
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Adobe
Data Scientist
June 16, 2026 – Present
A-B-Testing-Marketing-Promotions
November 29, 2020 – November 29, 2020
A-B-Testing-Marketing-Promotions — GitHub repository
View ProjectMarketing-Campaign-Analysis
April 26, 2020 – September 13, 2022
Checking the performance of campaigns on different marketing channels among control & experiment groups
View ProjectA-B-Testing-for-Impact-on-Website-Conversions
March 25, 2020 – March 25, 2020
A/B Testing to Determine Effect of Introducing Free Trial Screener on Conversions
View ProjectCustomer-Analytics_EDA_Bank-Marketing
October 18, 2019 – October 18, 2019
Exploratory data analysis to get a sense of the bank marketing dataset and see distribution of target variable (subscriptions/conversions) WRT important predictor variables like age-group, education, marital staus etc.
View ProjectProphet-Time-Series-Forecast-of-Articles-Posted-on-a-website
September 19, 2019 – September 19, 2019
Time series forecasting using facebook prophet for blog articles posted on a popular website
View ProjectCustomer-Analytics-EDA
September 4, 2019 – September 4, 2019
EDA of UrbanClap's bookings dataset: Calculation & Visualization of metrics like 1//3/6 months repeat rates, new customer acquisition, bookings by slot and by source
View ProjectTelecom-Churn-Prediction
July 16, 2019 – April 26, 2020
A classification project for forecasting the customers who are likely to churn. Random forests, XGBoost, SVM's used.
View ProjectCar-Price-Prediction-Highly-Comprehensive-Linear-Regression-Project-
June 30, 2019 – July 28, 2020
A Linear Regression model to predict the car prices for the U.S market to help a new entrant understand important pricing variables in the U.S automobile industry. A highly comprehensive analysis with detailed explanation of all steps; data cleaning, exploration, visualization, feature selection, model building, evaluation & MLR assumptions validity.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and focus on common data science problems, which indicates a foundational interest in the field. However, the lack of diverse project types beyond typical supervised learning and A/B testing, and the absence of team-based projects, limits the assessment of cultural fit and collaboration potential. The experience level is listed as 0, despite a current role at Adobe, which creates an inconsistency. The target role is 'Data Scientist', which aligns with the project types.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, indicating no assessment was completed.