Aug 2023 – Present · 2 yrs 8 mos · Remote

• The course features practical lessons heavily that we derived from two decades of working on some of the world's hardest forecasting problems at Amazon retail, Zalando and for AWS and its customers. You'll pick up the necessary theory, get hands-on example and learn about the tricks of the forecasting trade.
• https://maven.com/tim-januschowski/modern-forecasting

Dec 2022 – Jul 2023 · 7 mos

Jan 2022 – Feb 2024 · 2 yrs 1 mo · Berlin, Germany

Jan 2022 – Jan 2024 · 2 yrs

Mar 2018 – Dec 2021 · 3 yrs 9 mos · Berlin Area, Germany

• Part of AWS AI, in particular the AWS AI Labs group.
• My teams develop new algorithms and models for business problems involving (but not limited to) time series analysis. Development is holistic in the sense that we invent new algorithms and then bring them to production and operate them. The main areas include forecasting, anomaly detection and classification for products such as Lookout for Metrics, DevOps Guru, Forecast and others. At the same time, we engage with the scientific community regularly via publishing at NeurIPS, ICML and giving tutorials at venues such as SIGMOD and VLDB.
• In the past, I have managed engineering teams:
• MXNet Edge team: deep learning engine engineering team working with Apache MXNet on edge devices
• DevOps Guru Berlin engineering team (ramping it up)
• interim skip-level manager for Amazon Personalize science (recommendations)

Apr 2016 – Mar 2018 · 1 yr 11 mos · Berlin

• Part of Core Machine Learning (later Core AI) Team under Ralf Herbrich.
• cross-org/divisional project management ranging from short- to long-term engagements
• remote team management
• coverage of entire product pipeline: ideation, prototyping, productization, dev-ops
• coverage of tech stack includes: deep learning , statistical models, distributed systems/data systems (e.g., Spark, Mesos, AWS services), data science tools (e.g., Spark ML, python data science stack, Tableau)

Sep 2013 – Apr 2016 · 2 yrs 7 mos · Berlin

• Covering all aspects of building a demand forecasting system for Amazon-scale
• research on models & algorithms
• system engineering & software design
• implementation
• deployment
• operation & monitoring

Sep 2011 – Aug 2013 · 1 yr 11 mos · Potsdam

• Researching and developing applications of in-memory databases for compute-intensive tasks such as discrete optimization and forecasting within SAP's Innovation Center in Potsdam (founded in 2011).

May 2011 – Sep 2011 · 4 mos

Jan 2008 – Apr 2011 · 3 yrs 3 mos

• Title of thesis: Aspects of Static Symmetry Breaking
• Supervised by Marc van Dongen (UCC) and Barbara Smith (Leeds). The thesis is about symmetries and symmetry breaking in integer progamming, constraint programming and hybrids thereof. I show how static symmetry breaking can make algorithms more efficient from both a theoretical and a practical perspective.

Jan 2007 – Jan 2009 · 2 yrs

• Teaching assistant for varous courses in the Department of Computer Science and the School of Mathematics (both UCC): tutorials, practicals and lectures

Sep 2005 – Nov 2007 · 2 yrs 2 mos

• implementation of heuristics for a combinatorial optimization problem
• theoretical work on symmetries for integer programms

Jan 2002 – Jan 2007 · 5 yrs