Skip to content
View robbsson's full-sized avatar
  • Poland

Block or report robbsson

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
robbsson/README.md

Robert Pikala ✋

I am a Data Scientist and Qualified Actuary (license no. 367) with 7+ years experience in Actuarial Science, Data Analytics and Machine Learning with a strong mathematical background. Expert in statistics and data enthusiast continuously improving skills and looking for new ways to tell a good story using data.

About me

  • 💻 I am currently working as an Actuary.
  • 📧 robert.pikala@gmail.com
  • 🖥️ 📊 I am mastering Python skills.
  • ❔You can ask me about Data Science.

Connect with me:

amado-de-jesús-vázquez-acuña

Popular repositories Loading

  1. robbsson robbsson Public

  2. car_pricing_app car_pricing_app Public

    Python

  3. advanced-genai-actuarial advanced-genai-actuarial Public

    Forked from simonhatzesberger/advanced-genai-actuarial

    Hands-on Jupyter notebooks for the EAA seminar "Advanced Applications of Generative AI in Actuarial Science" (Vilnius, 1–2 October 2026): LLM basics and techniques, then five case studies from clai…

    Jupyter Notebook

  4. Actuarial-AI-Case-Studies Actuarial-AI-Case-Studies Public

    Forked from IAA-AITF/Actuarial-AI-Case-Studies

    A curated collection of actuarial AI case studies covering machine learning, generative AI, agentic AI, and more, designed to support actuaries in applying AI to real-world problems.

    HTML

  5. mega-s01e03-support-kb mega-s01e03-support-kb Public

    MEGA.dev S01E03: support kb with #4471 split into three problems

    Svelte