Berndt Lindner

WORK HISTORY

EDUCATION

SKILLS

ABOUT BERNDT LINDNER

TLDR- Global Talent (Tech Nation Visa) Alumni:\"Best tech talent from around the world to work in the UK’s digital technology sector, contributing their cutting edge expertise and creative skills\"- Tackle the well known, but not talked about enough, problem that 95% of models to do not reach production- Full-Stack AI Data Specialist: Expertly bridging Data Engineering, Statistics, Machine Learning, and the niche field of Optimal Decision Making (Operations Research) and more recently using AI Agents for analysis and workflow improvements- Proven track record in Energy, Retail, Telco, Travel, and Logistics—building robust, cloud or on-prem systems designed for longevity and ROI-I thrive in translating complex analytics into clear operational advantages. I\'ve work across the entire Analytics Ascendancy Model, having experience in data engineering, statistics, machine learning, and other areas of AI—including the niche field of optimal decision making (operations research). I try to always not just just diagnose/predict what will happen; but build solutions that decide exactly what to do about it.Most of these solutions are still driving value 7+ years post-launch, including- Retail: A markdown price optimization engine resulting in an 18% profit increase across a continental rollout- Telecommunications: A cell tower placement optimization tool, reducing infrastructure costs by 37%- Banking: Automated data validation pipeline application, reducing a 4-day manual process to 30 minutes with 100% accuracy.I implement principles and workflows to tackle the well known but usually overlooked stat that around 95% of AI (GAI, ML, etc) models do not reach production or add value, in short by POC -> MVP -> Production with iterative feedback.More recently, I’ve moved into leadership roles—managing and guiding advanced analytical development teams, projects, and products. When needed I remain deeply hands-on with the infrastructure that powers these insights, notably setting up and maintaining data and algorithm pipelines within the cloud (notably more Google Cloud) as well as more native/niche applications. I am also currently looking at the frontier of automation, namely building and using AI agents for sophisticated analysis and workflow improvements.