Michał Woźniak, PhD

Data Science Domain Manager @InPost | Asst. Prof. @U. of Warsaw

Warsaw, Mazowieckie, Poland

About

Experienced Data Scientist with profound knowledge of Econometrics and Machine Learning. Actively pursuing both professional and academic career paths. Realized numerous commercial quantitative projects in the insurance, e-commerce, and logistics industries. Experienced in leading analytics teams. PhD in Economics from the University of Warsaw, conducting research on the application of statistical learning in market risk estimation (academic social networks: https://linktr.ee/michalwozniak).

Experience

  • Data Science Domain Manager at InPost Group
    Mar 2025 - Present · 1 yr 5 mos

  • University of Warsaw (3 yrs 10 mos)
    • Assistant Professor
      Apr 2026 - Present · 4 mos

    • Lecturer
      Oct 2022 - Mar 2026 · 3 yrs 6 mos

      At the University of Warsaw, I teach the following courses: * Machine Learning in Finance I * Machine Learning in Finance II * Machine Learning 1: classification methods * Applied Finance - Risk modelling in financial institutions

  • InPost ()
    • Lead Data Scientist
      Feb 2024 - Feb 2025 · 1 yr 1 mo

    • Senior Data Scientist
      Apr 2023 - Mar 2024 · 1 yr

    • Data Scientist
      Jan 2021 - Mar 2023 · 2 yrs 3 mos

  • Senior Data Scientist at WeSub
    Feb 2023 - Dec 2023 · 11 mos

    As a scientific consultant specializing in forecasting model optimization, I was involved in the conceptualization, implementation, and deployment of a trading system utilized in the consumer electronics and home appliances sector.

  • PZU (2 yrs 6 mos)
    • Data Scientist at Innovation Lab
      Jul 2020 - Dec 2020 · 6 mos

      As a data scientist, I led and contributed to multiple projects across various domains, utilizing a wide range of machine learning techniques and tools. My key responsibilities and accomplishments include: - Developed a customer churn prediction model for corporate clients, solving a classification problem to identify potential churn risks and improve customer retention strategies - Optimized the process of actuarial risk measurement using an unsupervised learning approach to identify hidden patterns in data, improving decision-making accuracy - Built a predictive model for infectious disease incidence, applying time series analysis to forecast outbreaks and provide timely insights for healthcare planning - Modeled seller rankings for product training using ranking algos to evaluate and improve seller performance metrics - Developed a fraud detection model using similarity learning methods in computer vision, enhancing fraud detection efficiency through advanced pattern recognition - Conducted quantitative analysis of press texts using natural language processing (NLP) techniques, extracting insights for sentiment analysis and trend detection - Designed and implemented web scrapers/crawlers to collect data for real-time modeling and benchmarking purposes - Created dashboards and visualizations to communicate complex data insights and support business decision-making - Managed a team in the development of a real estate valuation model, overseeing the project from concept to delivery as the project manager - Led the creation of priority rankings for internal business initiatives in the field of machine learning, ensuring optimal allocation of resources and alignment with strategic objectives

    • Junior Data Scientist at Innovation Lab
      Jan 2019 - Jun 2020 · 1 yr 6 mos

    • Intern Data Scientist at Innovation Lab
      Jul 2018 - Dec 2018 · 6 mos