Jakub Švehla

• Working on an agentic AI assistant, which is a conversational analytics chatbot built on top of GoodData’s semantic layer, allowing users to talk to their data and do analytics.

• Built Simple Portfolio, which is a portfolio tracker SaaS with 20,000+ users and hundreds of paying customers, end-to-end, and now run it as a side project.

• Developed an LLM-based agent system to help with customer support tasks, such as ticket tracking, knowledge base extraction, or drafting replies.

• Developed a credit risk model and bank transaction categorization from a proof of concept to a production system.
• Built an LLM-based bank transaction anonymization pipeline.
• Developed a historized ML feature store on top of Databricks and Apache Spark.
• Optimized marketing budget allocation with Marketing mix modeling.

• Worked on detecting anomalies in network traffic using ML.

• Communicated with clients to identify and understand their problems and help them improve their processes and efficiency with data and AI.
• Led a data science team and helped hire and supervise new junior data scientists.
• Worked hands-on on many data science projects, primarily for large international bio- and agro-tech companies.
• Implemented many machine learning proof of concepts written in Python and Jupyter notebooks, using tools such as pandas, scikit-learn, SQL, Apache Spark, and various non-SQL databases.
• Deployed ETL and ML pipelines to production in the cloud.

• Helped prepare and lectured a graduate course on distributed data mining (both theoretical background and implementation in Apache Spark).
• Helped prepare and lectured a Python course for beginners (undergraduate).

• Worked on algorithmic/quantitative trading using machine learning.
• Applied machine learning algorithms to financial data.

• Worked on the backend that collected data from social networks (Facebook, Twitter, Instagram), stored, and analyzed them.
• Worked with various databases such as MySQL/PostgreSQL, MongoDB, HBase, or Redis.

Scaffold is a full-stack web framework that makes it easy to build apps following the Domain-Driven Design (DDD) approach and layered/onion architecture.

An open-source library implementing a wide range of active semi-supervised clustering algorithms for scikit-learn.