- Developed innovative solutions to address operational challenges, utilizing predictive analytics, machine learning, and optimization algorithms.- Successfully managed projects within the courier operations domain, ensuring adherence to timelines, budgets, and quality standards- Proficient in liaising with stakeholders to gather comprehensive requirements for projects, aligning solutions with business objectives- Skilled in executing end-to-end project implementations, delivering tangible outcomes that positively impact customer satisfaction and operational performance

As one of the first individuals employed at InPost as a Data Scientist, I had the opportunity to be part of the team's development process from its inception to becoming an integral part of the company. Throughout my journey, I have participated in several significant projects, such as:- Exploring the impact of the environment on parcel lockers- Forecasting parcel volumes- Optimizing parcel redirection- Customer profiling- Implementing an Enterprise Asset Management systemDuring my work on these projects, I utilized machine learning technologies, primarily Python and PySpark.

During my internship at UBS, I had the opportunity to work on predicting the profits of publicly traded companies. The outcomes of these analyses were subsequently utilized in the recommendations provided by stock market analysts. Throughout this process, I primarily utilized the R programming language.

My initial role related to data analysis provided me with the opportunity to collaborate with the accounting department in preparing data for settlements. Additionally, using the R programming language, I had the chance to develop an application for monitoring the status of vending machines.

Sales accountant.