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Engineering AI, Change Management, Innovation | Co-founder @
Data Science Society

NAME_1

Zusammenfassung
Machine Learning Engineer | Co-founder & CEO @ Data Science
Society | Innovation, Strategy, AI

Berufserfahrung
Data Science Society
5 Jahre 10 Monate
Chairman & CEO
März 2019 - Present (4 Jahre 4 Monate)
NAME_2
Co-Founder & Vice Chairman
September 2017 - März 2019 (1 Jahr 7 Monate)
NAME_2, Austria
• Manage key strategic issues, current opportunity assessment, gap
identification and accordingly plan and implement the society's initiatives and
marketing in coordination with the other board members.
• Reach out to and foster cooperative relationships with institutions, companies
and individuals in the domains of academia and business. Represent the
society by preparing and giving presentations.
• Research the needs and goals of our community and target group to create
course structures, syllabi and teaching approaches based on methodologies
with empirically proven effectiveness regarding factors of knowledge transfer
as well as student motivation and success.
• Drive for the implementation of efficient internal processes by introducing
applicable protocols from Scrum, Lean and Kanban.
A1 Telekom Austria AG
4 Jahre 6 Monate
Machine Learning Engineer
NAME_3 2020 - Dezember 2022 (2 Jahre 6 Monate)
NAME_2, Austria
Page 1 of 3
• Coordinated the company's largest data science project as a Agile Master
and instituted processes that facilitated results-focus, more effective
collaboration and skill transfer.
• Grew the scope of marketing automation capabilities by increasing the
volume (2X), velocity (hours->near real-time stream), variety and accuracy of
behavioral data related to digital interactions on the website, online shop and
in NAME_4.
• Engineered and optimized a terabyte-scale big data pipeline for rapid
analytical querying by data scientists (42X speed-up), faster ingestion
processing (2h->30mins) and decreased resource usage (1/2X compute &
memory; 1/3X HDFS storage).
• Developed streamlined best-practices guidelines, documentation structures,
and coded helper utilities that increase the speed and success chances of data
science & data engineering projects by facilitating results-focus and knowledge
transfer.
Developed and distributed a questionnaire-based tool for teams, which
facilitates increased performance by mea Do not include the following keywords: master, academia, relationship, scientist
user