Help & Supportcareers@gravityer.com
Ever learning analyst keen on using data science to solve marketing & customer analytics problems
AI is analyzing your overall score…
Identifying your key strengths…
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.