Jan Kislinger

Jan Kislinger

Data Scientist @ Peacock & Sky | PhD Researcher in Recommender Systems

About Me

I'm a passionate data scientist and mathematician specializing in recommendation engines. Currently pursuing a PhD at Czech Technical University, I focus on scalable multi-layered clustering for personalized streaming experiences.

Resume

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Experience Highlights

  • đź“… Data Science Manager @ Sky (Apr 2024 – Present): Leading a team of 4 building personalized sports recommendation pipelines.
  • đź“… Data Scientist @ Sky (Jun 2023 – Mar 2024): Localized and deployed recommender models across international markets.
  • đź“… Tech Lead @ Showmax (May 2020 – May 2023): Architected end-to-end ML pipelines (Airflow, Redis) for content personalization.
  • đź“… Data Science Lead @ Oddin.gg (Jul 2018 – Apr 2020): Developed real-time e-sports ML models via gRPC servers.

Education & Skills

  • 🎓 PhD Informatics @ Czech Technical University (2024 – Present)
  • 🎓 MA Probability, Statistics & Optimization @ Charles University (2017)
  • 🎓 BA Financial Mathematics @ Charles University (2014)

Technical Stack

Python TensorFlow Polars BigQuery Rust SQL Flask

Latest Blog Posts

Bringing the "Carousel" Experience to Recommender Systems

August 7, 2025

If you've ever opened your favorite app—whether for videos, music, shopping, or beyond—you’ve likely seen multiple rows—or "carousels"—of recommendations: “Keep Watching,” “Just for You,” “Hot Right Now,” and so on. Yet, much of the academic research out there still focuses on a single ranked list—a single column of suggestions.

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