Career Paths for you to Lead, Principal, and CDO.

Data Careers in the next ten years (1)

Senior Data Engineer IV

Senior Data Scientist

Senior Data Engineer III

Lead Data Scientist

Senior Data Engineer II

Senior Data Engineer

Head of Data

Senior Data Engineer

Director Data Platform

Science to Data Science: PhDs and postdocs moving to industry

Science to Data Science: PhDs and postdocs moving to industry

Science to Data Science: PhDs and postdocs moving to industry

Technical Profiles for Data Scientists

Science to Data Science: PhDs and postdocs moving to industry

MIssion Statements for Data Scientists

Technical Profiles for ML Engineers

Technical Profiles for Data Analysts

Science to Data Science: PhDs and postdocs moving to industry

Technical Profiles for Data Analysts

The Highest Standard for Technical Competency

Technical Profiles for Data Scientists

Mission Statements for Data Scientists

AI Guild Members' Office Hour

Applying? Examples of technical profiles on a CV.

Hiring 15+ Entry-level Roles (Science to Data Science)

Science to Data Science: PhDs moving to industry and startups

#datalift22 Lessons learned when hiring and retaining data professionals by Tereza Iofciu

#datalift22 Make it worth: how to successfully deliver ML to production by Inbal Budowski-Tal

#datalift22 The Quick & Dirty AI Startup by Noa Weiss

#datalift22 Regulatory guidance/AI transparency by Bruno Ohana

#datalift22 Taking AI from good to great by understanding it in the real world by Itai Bar-Sinai

#datalift22 What I learned from monitoring 30 Machine Learning Use Cases by Lina Weichbrodt

#datalift22 Embeddings paradigm shift: model training to vector similarity search by Nava Levy

#datalift22 Big & Growing - Empowering people in the age of technology by Tina Ruseva

#datalift22 Developing and monitoring AI solutions with limited labeled data by Justin Shenk

#datalift22 Enable Trust in AI through Testing by Florens Greßner

#datalift22 AI Governance in Practice by Rasmus Hauch

#datalift22 What kind of reskilling/hiring inis need to become AI-driven? by Nitin Kumar

#datalift22 How to teach Data Science? by Kristian Rother

#datalift22 Summit Berlin 22.-24. June Opening keynote

Science to Data Science for PhDs with employment contract and training

Artificial Emotional Intelligence in Finance: Shannon Kehoe

Empowering People in the Tech Age: Tina Ruseva

AI Governance in Practice: Rasmus Hauch

Industrial Machine Vision Applications: Markus Schatzl

Safety-Critical AI Applications: Mirko Knaak

Adaptive Large-Scale Recommender System: Evgeny Labzin

Flexibility in Energy Supply and Demand

Transformer models to forecast customer demand

ML Platform at GetYourGuide

A/B Experiments on a Scalable Platform: Eugene Klyuchnikov

Embeddings from Model Training to Vector Similarity Search: Nava Levy

Lessons Learned when Hiring and Retaining: Tereza Iofciu

AI-based dynamic pricing: Pouyan Fard