Help & Supportcareers@gravityer.com
Senior Data Scientist
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Experienced Research Scientist with a strong background in both groundbreaking artificial intelligence fundamentals research and high impact research application is the fashion retail space. Skilled in Python, Mathematics, Tensorflow and all things fashion retail. Currently holds a masters in Mathematics from the Humboldt University Berlin and is perusing a PhD in Machine Learning under Prof. Dr. Sepp Hochreiter at the Johannes Kepler University in Linz, Austria.
Johannes Kepler Universität Linz
Doctorate Studies , Machine Learning
January 1, 2016 – January 1, 2019
Humboldt-Universität zu Berlin
Master's degree, Mathematics and Computer Science
January 1, 2008 – January 1, 2012
Colorado State University
Master's degree, Mathematics
January 1, 2005 – January 1, 2006
HMS Analytical Software | Consulting & End-to-End Solutions for Data Science & Analytics
Senior Data Scientist
September 1, 2024 – Present
Berlin, Berlin, Germany
Bolt
Senior Data Scientist
November 1, 2022 – September 1, 2024
Berlin, Germany · Hybrid
Zalando
Applied Scientist with focus on Computer Vision and Reinforcement Learning
January 1, 2020 – November 1, 2022
Zalando
Research Scientist PhD with Focus on Deep Learning
September 1, 2016 – December 1, 2019
Zalando
Data Scientist with Focus on Warehouse Logistics
May 1, 2012 – September 1, 2016
Geomecon
Student Mathematician
April 1, 2011 – April 1, 2012
Potsdam Area, Germany
Invited Speaker at M3 Conference in Cologne -- AI successfully applied
April 1, 2018 – April 1, 2018
Rome wasn't built in a day. The same holds for Artificial Intelligence in your company. Every big player in the Artificial Intelligence space first optimized their core business before applying acquired knowledge to generate new AI powered business models. The amazing self driving cars and machine powered translations built upon successes of lane departure warnings and auto-complete. Starting with an example from warehouse logistics, we'll show how Zalando Research streamlined a core business process while building AI trust and knowledge in the company. Further, we discuss management strategies to secure the success of AI projects. Check out the slides at https://www.slideshare.net/CalvinSeward/ai-successfully-applied
Invited Speaker at AI Summit Vienna -- Deep Learning -- More than Classification
September 1, 2017 – September 1, 2017
Many of Deep learning's first big breakthroughs were in the field of classification, for example recognizing hand written digits or imagenet images. While such results were impressive, they are only a drop in the sea of possible deep learning applications, a sea who's extent we are only just now beginning to discover. In this talk, I'll demonstrate a sampling of and exciting deep learning applications we're working on at Zalando in cooperation with Prof. Dr. Sepp Hochreiter's team at JKU Linz. These include image generation with Generative Adversarial Networks, Semi Supervised Semantic Segmentation, Warehouse Optimization and Recommender Systems. I'll then wrap up with a few technical tips and tricks on how you too can start learning your own deep neural networks. Video: https://www.youtube.com/watch?v=oHve-AX8bPI Slides: https://mostly.ai/summit/slides/Zalando%20Calvin%20Seward.pdf
Invited Speaker at data2day Heidelberg -- Search at Petabyte Scale
September 1, 2017 – September 1, 2017
In vielen Big-Data-Anwendungen müssen riesige Datensätze schnell durchsucht werden, um relevante Information wie Kundenprofile, Bilder oder Dokumente zu finden. Der naive Suchaufwand wächst linear mit der Zahl der gespeicherten Daten: ein tödliches Problem für skalierbare Real-Time-Big-Data-Lösungen. Approximate-Nearest-Neighbor-Methoden (ANN) finden die gesuchten Ergebnisse mit hoher Wahrscheinlichkeit, bei zugleich exponenziell reduziertem Aufwand. Diese innovative Technologie ermöglicht erst die Skalierung datenintensiver Anwendungen in den Petabyte-Bereich. In meinem Talk werde ich die Basics von ANN erläutern und eine Bildersuche mittels einer Python-Open-Source-Toolbox demonstrieren.
Invited Speaker at TDWI Munich
June 1, 2017 – June 1, 2017
Title: Leveraging our Pictures: Deep Learning with Tensorflow at Zalando This business oriented talk motivates why data science and machine learning, especially machine learning on unstructured data such as images and natural languages is important for products to be competitive in future. The talk then shows some excited work we've done with images at Zalando research and ends with a quick demonstration of Tensorflow, a framework for easy GPU computing at scale. Click the link to get the slides.
Invited Speaker at Deep Learning in Retail & Advertising Summit London
June 1, 2017 – Present
Title: How Zalando Accelerates Warehouse Operations with Neural Networks This talk introduces a specific problem in the warehouse, the so called order batching problem, and demonstrates how we are able to find near optimal solutions by using machine learning tricks. It's interesting since we're able to apply neural networks outside of the domains they are generally used. The talk concludes with a point that is near and dear to me: only using machine learning to drive efficiency of existing business models leaves many game changing machine learning untapped. Click on link to view the talk. Bonus: there's a video!! watch it before it's pay-walled http://videos.re-work.co/videos/473-deep-learning-for-retail-warehouse-operations
Invited Speaker at Data2Day Karlsruhe
October 1, 2016 – October 1, 2016
Title: Leveraging our Pictures Deep Learning with Tensorflow at Zalando This talk shows an exciting application of Zalando's image data we've been working on at Zalando research which enables us to localize items in a picture without any prior localization training information. The talk concludes with a quick and practical demonstration of Tensorflow, a framework for easy GPU computing at scale. Click the link to get the slides.
Optimizing Warehouse Operations with Neural Networks on GPUs
March 1, 2015 – October 1, 2015
https://devblogs.nvidia.com/parallelforall/optimizing-warehouse-operations-machine-learning-gpus/ We trained a neural network to predict the length of pick routes through the warehouse. Then enables us to quickly try many different combinations of warehouse locations in order to create optimal batches.
OCaPi -- Optimal Picker Routing with Cart
June 1, 2014 – March 1, 2015
https://tech.zalando.com/blog/defeating-the-travelling-salesman-problem-for-warehouse-logistics/ In order to tell guide pickers optimally through the warehouse, we developed a system that finds the optimal route to walk through the warehouse and how pickers can to best manage their carts, resulting in a significant boost in pick performance.
Startup Engineering -- Online Web Development Class
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including multiple speaking engagements and applied research, demonstrates a proactive and knowledge-sharing attitude. Their experience across different companies (Zalando, Bolt, HMS Analytical Software) and roles (Research Scientist, Applied Scientist, Senior Data Scientist) indicates adaptability and a broad understanding of data science applications in various business contexts. The deep academic background combined with practical industry experience suggests a strong fit for a role that values both innovation and execution. The focus on solving real-world problems aligns well with a results-driven culture.
Soft Skills & Operational Fit
The candidate's extensive experience in leading data science initiatives, presenting at conferences, and collaborating with various departments (as described in Zalando roles) suggests strong communication, problem-solving, and stakeholder management skills. The focus on optimizing business processes with data science indicates a results-oriented and operationally aware mindset. The academic background and research experience point to a strong analytical and critical thinking ability.