Full-Stack Analytics Engineer: Data & BI Engineer | Data Analyst

12/2022 – offen

• Daily briefings and reports on trip planning productivity by leveraging PowerBI dashboards and Python to derive actionable data-driven insights to senior executives, leading to strategic operational improvements.
• Assisting the Data Science team with new prediction models, feature engineering and model evaluation dashboards, contributing to an approximately 30% enhancement in the F1-Score for the trip lengths estimator.
• Managing end-to-end ETL pipelines in Databricks PySpark (DLT), cleansing and enriching raw data, defining schemas, optimizing storage, and fostering collaboration across teams for seamless and efficient data analysis.

Azure Databricks, Microsoft Power BI, SQL, Python

7/2021 – 11/2022

Research topic: hybrid recommender system based on heterogeneous implicit feedback (Python, Google BigQuery, Google Analytics)

• Churn Prediction: Building a churn prediction model to classify highly risked customers and proactively develop marketing strategies as churn prevention measurements.
• Customer Segmentation: Using unsupervised learning to segment customers based on ordering behaviour (Recency, Frequency, Monetary) and automate daily segmentation pipeline into Google BigQuery through Cronjobs.
• Google Analytics: Assisting product managers with determining and monitoring KPIs for new app releases through Google Analytics data.
• Push Notification Automation: Identifying abandoned baskets and sending out automated push notifications to increase conversion and decrease order completion duration through an API.
• Attribution Model: Identifying and assigning credit to marketing touchpoints during the customer journey to evaluate and compare customer communication funnels.

Data Science, Business Intelligence (BI), Datenanalyse

2/2019 – 9/2020

Improving and monitoring processes in fulfilment based on data and operational analysis:

• Building dashboards to steer daily fulfilment operations (i.e. operations efficiency, employee productivity).
• Monitoring of and reporting on recruitment efficiency for Fulfilment Centers.
• Stakeholder management of temporary employment agencies.
• Development of communication channels to automate People Operations processes through Google Apps Script.
• Automation of communication of weekly payment process results through Python and Gmail API.
• Building an API to automate the approval process of employees' working hours in Fulfilment Centers and Hubs by respective supervisors.

Business Analyse, Datenanalyse