David Grigorev Email & Phone Number

Stack: Python, SQL, Redash, Git, Tableau.Project 1: Analysis of consumer behavior and audience segmentation.Project Objectives:- Conduct cohort analysis to determine retention rate;- RFM segmentation of users;- Analysis of user activity.Tools Used: Python (Pandas, Numpy, Seaborn, Matplotlib)Work Stages:- Data preprocessing and exploration;- Calculation of various order metrics (undelivered orders, single orders, various averages);- Conducted cohort analysis, calculated retention rate;- Conducted RFM segmentation.Results:- Determined the most common day of the week for each product purchase;- Calculated the average number of purchases per week for each user;- Conducted cohort analysis by months, identified the cohort with the highest retention rate at 3 months;- Built RFM segmentation. Defined the boundaries of recency, frequency, and monetary metrics for interpreting these clusters for each RFM segment;- Visualized key analysis results for clear data presentation and facilitation of decision-making for stakeholders.Project 2: HR Department Dashboard.Project Objectives:Build a dashboard for effective distribution of bonuses among employees.Tools Used: TableauStages:- Gathered information and requirements from the client, outlined a canvas to describe the project.- Created graphs in Tableau (Bar chart, interactive tables, factoids for key metrics).- Built the dashboard.- Results: Constructed a dashboard with filtering capabilities and the ability to perform necessary calculations.Project 3: Analysis of avocado sales in the USA.Project Objectives:Create a dashboard for the avocado sales department in the USA to analyze sales.Tools Used: SQL ClickHouse, Redash.Stages:- Data exploration, identifying patterns.- Building SQL queries.- Constructing charts.- Creating a dashboard from the generated charts.Result: A dashboard was built using Redash for sales analysis. Five charts were utilized (Line chart, Bar chart, Pie chart).

Project: App Metrics Insight (Retention rate & A/B testing)Project Objectives:Development of a function to calculate player retention rate.Analysis of the results of A/B testing of various sets of promotional offers.Proposal of metrics for analyzing thematic events in the game.Tools Used: Python (Pandas, Numpy, Seaborn, Matplotlib, Scipy.stats)Stages:- Data preprocessing and exploration.- Development of a function to calculate retention rate.- Selection of statistical tests.- Formulation of hypotheses.- Conducted research (T-test, Chi-square method).- Identification of possible metrics for analyzing thematic events.Results:- A fully functional function for calculating retention rate, with the ability to choose the time interval for calculating the indicator.- Conducted research on the results of the A/B test. The best promotional offer was identified.- Metrics for analyzing thematic events in the mobile game were identified.Project: A/B Testing.Project Objectives:Evaluation of a new recommendation system through statistical comparison of metrics in two groups to make a decision on rolling out the new system to all users.Tools Used: Python (Pandas, Pingouin, Numpy, Seaborn, Matplotlib, Scipy.stats, Statsmodels)Stages:- Preliminary data exploration.- Selection of metrics for comparison in two groups.- Selection of statistical methods.- Formulation of hypotheses.- Conducted tests.- Drew conclusions and visualized the results.Results:The new recommendation system was evaluated, and based on statistics, we were able to conclude that the new system could positively impact key metrics.

St Petersburg, St Petersburg City, Russia

Internship at SKS - a company specializing in the sale of climate control equipment.During the internship:- I conducted analytics on the company's logistics costs;- Optimized processes for transportation and warehousing of goods.Results:- I Developed an EOQ (Economic Order Quantity) model from scratch;- Created a plan with recommendations for reducing logistics costs by 33% (forecast);- Presented the model to the management.Internship at VEZU - a transportation company.During the internship:- I monitored approximately 100 vehicles (trucks) with cargoes simultaneously.- Resolved around 25 unexpected situations during cargo transportation.Results:- I initiated the optimization of the vehicle monitoring process, reducing dispatcher errors by 50%:- Conducted an analysis of the process and identified the reasons for errors;- Introduced a new, more logical system for organizing data in Excel;- Developed an instruction manual for the updated process in the form of a checklist.Internship at "No Barriers Wheelchair" - a non-profit organization.During the internship:- I Was responsible for developing the product strategy.- Managed a project for organizing the production and sales of merchandise (own products) for the non-profit organization.- Developed the concept and formulated the technical task;- Conducted market analysis, researched merchandise manufacturers, and distribution channels.