Senior Data Scientist · PhD Mathematician · Educator

Robert Kübler

Dr. Robert
Kübler

I set technical direction for ML teams, ship forecasting systems, translate complex models into business outcomes, and grow the people around me. PhD in mathematics. 7+ years at the intersection of research, production, and teaching.

5+
Years in Senior ML Roles
€10M+
Revenue Impact
50+
Professionals Taught
1M+
Article Reads
Lead
Technical direction, engineering standards, mentoring junior scientists
Build
Forecasting, recommenders, causal inference in production
Teach
90+ articles, official ML curriculum, 1M+ readers

/ About

Research depth. Production reality.

Hi, I'm Robert. I'm a Senior Staff Data Scientist at ALDI DX, where I set the technical direction for a supply chain forecasting product optimizing warehouse staff planning across 150+ time series. I also mentor data scientists, design and deliver official ML curricula, and write for a 1M+ readership. My PhD in mathematics gives me the depth to go from a whiteboard proof to a production model without losing either rigour or pragmatism.

I care deeply about sharing what I know and making the people around me better.

90+ articles on Medium with 1M+ reads, the official sktime forecasting curriculum for the German Center for Open Source AI, talks at data science meetups (Zalando, Inovex), and contributions to open-source libraries like scikit-lego and PyMC-Marketing.

/ Experience

Roles & impact

Employment

Sep 2024
Present
ALDI DX
Mülheim an der Ruhr
Senior Staff Data Scientist
  • Set the technical direction for a supply chain forecasting product optimizing warehouse staff planning, and championed sktime adoption beyond the immediate team, driving uptake across additional teams in the organization
  • Introduced sktime to replace a Prophet-only setup, achieving a 10% reduction in offline MAPE across 150+ time series to improve workforce allocation
  • Drove the adoption of rigorous engineering standards (unit testing, Ruff, Black) across 40+ data scientists, reducing technical debt and ensuring long-term maintainability
Jan 2022
Aug 2024
METRO.digital
Düsseldorf
Senior Data Scientist Oct 2023 – Aug 2024
Assortment Optimization
  • Built a causal inference framework (S-learner) for assortment optimization, automating product delisting
  • Mentored junior and mid-level data scientists
Senior Data Scientist Jan 2022 – Sep 2023
Product Recommender
  • Built two real-time recommender systems (two-tower, TensorFlow) trained on billions of transactional rows, deployed on GCP / Vertex AI, driving €10M+ in annual revenue; validated via A/B testing (GrowthBook)
  • Led technical hiring: screened 20+ candidates, co-led 5 interviews, onboarded 3 hires
  • Mentored 3 data scientists and led upskilling events for a team of 20
Sep 2020
Dec 2021
MEDION AG (Lenovo)
Essen
Senior Data Scientist
  • Developed and open-sourced mamimo, a marketing mix modeling package (74 GitHub stars); results directly influenced marketing budget allocation
  • Owned 3 analytical workstreams end-to-end: forecasting (Prophet, LightGBM, QlikSense dashboards), MMM, and causal inference
  • Mentored 2 junior data scientists
Jun 2019
Aug 2020
Publicis Media
Düsseldorf
Data Scientist
  • Predicted TV ad view-through rates for media clients: modeled what share of an advertising block audiences would watch
  • Joined datasets without a common identifier using statistical record linkage (Nearest Neighbor matching)
  • Built the data backend for a competitive benchmarking dashboard, enabling a client to compare performance against direct competitors across key metrics
Apr 2018
May 2019
HSBC
Düsseldorf
Trainee Risk
  • Automated processes in Risk and Cyber Security (Python, SQL, VBA), eliminating 2 FTE-equivalent manual workloads

Freelance

Mar 2024
Present
ScanmarQED
Remote
Consulting Data Scientist (Part-Time)
  • Part-time advisory and backend engineering (PyMC-Marketing) for a SaaS analytics platform; engagement continued under ScanmarQED after its acquisition of MMMLabs.ai (Feb 2026)
Apr 2025
Present
GC Open Source AI
Remote
Guest Instructor & Open-Source Contributor
  • Design and deliver the official sktime curriculum across 3 cohorts (15 professionals)
  • Active open-source contributor: identified and fixed critical bugs in make_regression and ForecastKnownValues; proposed improvements to StackingForecaster, pipeline caching, and GroupByTransformer
2019
Present
Medium, VectorHub, KDNuggets
Remote
Technical Author
  • 90+ articles on data science and ML topics, with 1M+ total reads across platforms

/ Writing

Technical articles

All articles →
1M+

people have read my work across 90+ articles on forecasting, Bayesian methods, recommender systems, and applied ML.

90+ Articles published
5k+ Medium followers
6+ Years publishing
41k views
Upgraded Marketing Mix Modeling
A deep dive into modern MMM techniques, moving beyond simple regression into Bayesian approaches.
39k views
Extensible Evolutionary Algorithms
Building flexible evolutionary algorithm frameworks in Python for real-world optimization problems.
34k views
The Explainable Boosting Machine
As accurate as gradient boosting and as interpretable as linear regression.
32k views
Embedding-Based Recommender Systems
How two-tower neural architectures power modern product recommendation at scale.
28k views
Where Machine Learning Meets Cryptography
Solving the cryptographically-relevant Learning Parity with Noise problem via machine learning.
27k views
Zero-Inflated Regression
Modeling count data with excess zeros: theory, implementation, and practical use cases in scikit-lego.

/ Projects

Interactive demos

Web PyTorch Next.js TypeScript D3.js
Parlascanned
Voting patterns, party demographics, and side income of all Bundestag members: three interactive views into the German parliament.
Launch demo →

/ Skills

Areas of expertise

ML & Mathematics

Reasoning from first principles

Probabilistic thinking, Bayesian inference, and theoretical foundations applied to real forecasting and decision problems.

Forecasting Causal Inference Bayesian Statistics Deep Learning Recommenders MMM Optimization Probability Theory Algorithms Number Theory

Leadership & Vision

Setting direction, growing people

Bridging research and product: defining technical strategy, mentoring engineers, and making complex ideas land with any audience.

Technical Vision Team Mentoring Engineering Standards Technical Writing Curriculum Design Public Speaking Stakeholder Communication Agile / Scrum International Teams

Engineering

Building reliable systems

Turning research-grade ideas into production-ready, maintainable systems on modern cloud infrastructure.

Python TensorFlow PyTorch PyMC GCP Vertex AI MLflow Docker PySpark SQL pandas sktime

/ Publications

Research papers

Google Scholar →
2021
FSTTCS 2021
A Faster Algorithm for Finding Closest Pairs in Hamming Metric
  • Presents a faster randomized algorithm for finding the closest pair of vectors under Hamming distance, with improved complexity for small dimensions relative to dataset size
Publication PDF
2018
PhD Dissertation
Time-Memory Trade-offs for the Learning Parity with Noise Problem
  • Investigates algorithms that trade memory for runtime when solving the LPN problem, a hard problem underlying several post-quantum cryptographic schemes
PDF
2018
CRYPTO 2018
Dissection-BKW
  • Applies dissection techniques to the BKW algorithm for solving LPN, improving the memory-runtime tradeoff
Publication PDF
2017
CRYPTO 2017
LPN Decoded
  • A unified framework for analysing and comparing LPN solvers, introducing the first quantum algorithm for LPN and demonstrating practical attacks on medium-parameter instances
Publication PDF

/ Education

Academic background

2015
2018
Ruhr University Bochum
PhD, Mathematics (Cryptography)
  • Dissertation: Time-Memory Trade-offs for the Learning Parity with Noise Problem, focusing on memory-efficient algorithms for the cryptographically relevant LPN problem
  • 3 peer-reviewed publications (CRYPTO 2017, CRYPTO 2018, FSTTCS 2021)
  • Taught cryptography, number theory, discrete mathematics; supervised 5 theses
2012
2014
Ruhr University Bochum
MSc, Mathematics · Minor: Computer Science
  • Grade: 1.2 (top 5%)
2013
2014
Osaka University
Exchange
Japanese Language & Culture
  • Japanese language: A1 → B1
2009
2012
Ruhr University Bochum
BSc, Mathematics · Minor: Computer Science
  • Grade: 1.0 (top 5%)

Recognition

Dobbertin Challenge DAAD Scholarship DMV Abitur Prize JASSO Scholarship

Certifications

CS191x: Quantum Computation CS188.1x: Artificial Intelligence Advanced NLP with spaCy Azure Fundamentals

Languages

German: Native English: Full Professional Japanese: Basic Conversations

/ Volunteer

Giving back

Jan 2007
Apr 2019
Vorhilfe.de e.V.
Moderator, matheraum.de
  • Supported school and university students with mathematical questions over 12 years
May 2021
Sep 2021
TechLabs Düsseldorf
Data Science Mentor
  • Guided aspiring data scientists through an end-to-end project predicting used car prices

/ Contact

Get in touch

Open to speaking engagements, collaborations, and selected consulting around data science, forecasting, and causal inference. Also happy to chat about articles or open-source work.