Deliv Inc., Data Analyst, Menlo Park (CA) 2019–Present
Created and implemented various statistical, predictive models to forecast volume, drivers, maintain driver retention and reduce driver attrition
Developed a system that can capture the anomalies in the forecast data and sends timely alerts to the team
Built a regression model that can accurately estimate the unit cost of order delivery based on the volume change for the following weeks
Correlation analysis to understand the relationship of forecast variance and cost
Problem solve how specific metrics need to be generated and, when required, work with the product and engineering teams to implement solutions (e.g. data gathering, gap analysis, work on submitted feature request or business requirement documents, file bugs etc.)
Simulated data of new accounts to determine the costing and pricing to determine if an account will be profitable to launch with Deliv retailer network Deliv Inc., Operations Intern, Menlo Park (CA) 2018–2019
Create new or reorganize existing scenarios, for example, consolidating delivery service regions and extending driver pool to assess potential expense and administration level consequences for the existing network
Gauge potential cost impact of new service launches on the current network
Market cost and profiles were determined by applying linear and non-linear regression to the historical delivery data
Developing network optimization and pricing tool
Worked on call center and dispatcher optimization Turkish Airlines (Miles and Smiles Loyalty Program), Istanbul 2016–2017
By using clustering analysis, association rule and apriori algorithm, campaigns were sent to the correct customer base.
Calculated customer value by RFM to make correct classification of customers.
New campaign types were created by searching literature and trends
New campaign types such as personnel campaigns were simulated and analyzed.
Increased email seen rate by the customers around %60 by using A/B test.
Worked on improving e-mailing operations by analyzing campaign success rate.
Next year's forecasted campaign schedule was prepared by using regression analysis of customer and flight data.
Bosch Thermotechnology (Sales Department), Istanbul Aug 2016-Sep 2016
Analyzed sales data for Turkey and prepared reports to make sale recommendations
Adapted sales disciplines
Visited dealers and experienced real-life sales events
Prepared contracts for sales team
Estimated year-end market share by using market data statistics
Conducted market research for new products planned to be produced firstname.lastname@example.org
Work Authorization: Green card
Michael Hart (COO at Deliv)
Soumya Badam (Sr. Data
Lutfi Ucar (Sr. Data
Udacity Data Science Nano
Probability and Statistics for
Business and Data
Computer skills: Python,
Pandas, SQL, Tableau, MS
Statistical Modeling: Statistical
Tests (t-test, Chi-Square test,
Experience in Data Analysis, Statistical Analysis, operations, data analytics, and network optimization
Eager to learn new tools, languages, and frameworks
Passionate to take on new challenges
BSc, Dogus University, Industrial Engineering, 2012-2018