Alptekin Uzel

Rider & Forecasting data science team in the Logistics Department. - Forecasting order demand in 40 countries. Time series & regression techniques. - Predicting rider demand metrics with multi output regression. - Leading rider payments projects using: Price elasticity and optimization. - Developing new models from scratch. - Leading business stakeholder management and project management. - Hands on deployment and maintenance of models. Tools: Python, Airflow, Metaflow, AWS, SQL (BigQuery)

Data Scientist in Growth & Marketing team of the leading e-commerce platform. Responsible from personalization of the e-commerce experience via machine learning models: propensity models, price elasticity, recommendation and sales forecasting.

Developing and deploying machine learning models with historical mobility data (up to last 5 years). Visualization and analysis of traffic congestion data. Also clustering and scoring of regions. Time series forecasting with geospatial data. Helping to develop location intelligence solutions for PropTech, retail and logistics. Business development and product management. Leading operationalization of data analytics as well.

Billing and payments domain expert. Billing software configuration, analysis and support for software development projects. Worked closely with product managers, scrum masters and developers.