Thorben Schlätzer
I'm enabling the financial industry to increase their business value through data.
Thorben Schlätzer
I'm enabling the financial industry to increase their business value through data.
After reviewing the application process in many different industries, I decided to tackle the problem
of complicated cover letters and CVs. My goal is to be able to analyze job offers and use the important
keywords to automatically generate well-written cover letters and offer perfect design combinations for both,
cover letters and CVs.
This way, I want to enable every applicant to not fear bad first impressions and
highlight their knowledge and experience to be taken into consideration.
Projects and Techniques used for this project:
- | „Text Preprocessing Pipeline“ (open) |
- | „Text Feature Extraction Pipeline“ (open) |
- | „Traditional Text Classification“ (open) |
- | „Deep Text Classification“ (open) |
- | „Web Data Extraction for Job Applications“ (open) |
Thorben Schlätzer
Applivo.de
Lerchenweg 5
50997 Köln
Telefon: 0178 203 15 77
E-Mail: kontakt@thorbenschlaetzer.de
Die Europäische Kommission stellt eine Plattform zur Online-Streitbeilegung (OS) bereit: https://ec.europa.eu/consumers/odr.
Unsere E-Mail-Adresse finden Sie oben im Impressum.
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NLP is a very interesting approach of AI in the financial industry.
Given that there are a lot of contracts and legal documents to take into account for daily business,
NLP helps to structure the information.
Great applications can be seen in text classification,
document summarization, search algorithms, automatic translation or even text generation.
My contributions to NLP:
- | Bachelor's thesis: „Natural Language Processing als Effizientreiber der Versicherungsbranche“ / „Natural Language Processing as an efficiency driver for the insurance industry“ |
- | Contribution to the book „Insurance & Innovation 2019“ (coming out in May, 2019), chapter „Natural Language Processing für die Versicherungswirtschaft“ / „Natural Language Processing for the insurance industry“ - Prof. Dr. Torsten Rohlfs & Thorben Schlätzer |
- | Project: „Text Preprocessing Pipeline“ (open) |
- | Project: „Text Feature Extraction Pipeline“ (open) |
- | Project: „Traditional Text Classification“ (open) |
- | Project: „Deep Text Classification“ (open) |
If you want me to contribute to your business' value, please contact me:
RL probably is the closest approach to Artificial General Intelligence. The goal is to train an agent/bot in an environment, which it doesn't know about. The idea behind this method is to give feedback for every action the agent performs in order to let the agent learn from trial and error. This interaction leads to very satisfying results and the development of Deep Learning in that context helps to beat human "agents" in some tasks really well (e.g. AlphaGo).
My contributions to RL:
- | Project: „Deep Reinforcement Drone Agent“ (open) |
If you want me to contribute to your business' value, please contact me:
Due to the rise of the information age like I like to call modern days, the unstructured data is increasing everyday - in a rather exponential manner. Making use of this data and consciously structuring it, helps to make use of data businesses haven't had access to before. To be able to use data to increase business value, we need a lot of structured data which we can then use again to transform unstructered data. All in all, techniques to make use of data can be very important for businesses. I developed techniques to effectively gather useful information.
My contributions:
- | Project: „Web Data Extraction for Job Applications“ (open) |
If you want me to contribute to your business' value, please contact me:
| Personal Information |
Birth | February 10th, 1993 |
City | Cologne, Germany |
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| Educational Records |
2019 | Machine Learning Engineer Certification |
| Degree: Udacity Nanodegree |
| Duration: 6 months |
| Skills: Machine Learning techniques, Neural Networks, Deep Reinforcement Learning |
| Link to Certification: Here |
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2019 | Deep Learning Certification |
| Degree: DeepLearning.ai Specialization |
| Duration: 4 months |
| Skills: Sequential Neural Networks, Convolutional Neural Networks, Hyperparameter Tuning, Machine Learning Project Management |
| Link to Certification: Here |
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2019 | Data Science Math Skills |
| Duration: 4 weeks |
| Skills: Functions & Graphs, Rates of Change, Intro to Probability Theory |
| Link to Certification: Here |
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2019 | Mathematics Certifications |
| Degree: Mathematics for Machine Learning Specialization |
| Duration: 3 months |
| Skills: Linear Algebra, Multivariate Calculus, Statistics |
| Link to Certification: Here |
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2018 | Data Analyst Certification |
| Degree: Udacity Nanodegree |
| Duration: 6 months |
| Skills: Python, R, Statistical Analyses, Data Wrangling |
| Link to Certification: Here |
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2018 | Bachelor, Sc. in Insurance Management |
| University: University of Applied Sciences, Cologne |
| main study areas: Risk Management, Accounting, Reinsurance |
| Bachelor's thesis: „Natural Language Processing als Effizientreiber der Versicherungsbranche“ / „Natural Language Processing as an efficiency driver for the insurance industry“ |
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2015 | Versicherungsfachmann / Insurance Professional Certificate |
| Degree: IHK degree / Degree of the Chamber of Commerce, Hannover |
| Duration: 6 months |
| Skills: Insurance Contracting, Insurance Advisory, Risk Advisory |
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2015 | Apprenticeship at Sparkasse Paderborn Detmold |
| Company: Local Bank, 1,500 employees |
| Location: Paderborn, Germany |
| Degree: Bankkaufmann / Certified Banker |
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2012 | High School degree |
| Location: Paderborn, Germany |
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| Professional Experience |
NOW | Working student for ISS Software GmbH |
| Company: Insurance Software Development, 100 employees |
| Location: Cologne, Germany |
| Duration: since July 2018 |
| Tasks: AI-empowered projects, Bachelor's thesis |
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2017 | Working student for InsurLab Germany e.V. |
| Company: largest networking platform for InsurTechs and Corporates in Germany, 10 employees |
| Location: Cologne, Germany |
| Duration: 12 months |
| Tasks: Helping to build up the initiative, insurance contracting, organizing the accounting, support for technical issues |
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2016 | Working student for Carl Jaspers Versicherungskontor GmbH |
| Company: Industrial insurance broker, 25 employees |
| Location: Cologne, Germany |
| Duration: 9 months |
| Tasks: Preparing Analyses for Risk Advisory, Supporting Sales, Risk Management Support |
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2015 | Bank clerk at Sparkasse Paderborn Detmold |
| Company: Local Bank, 1,500 employees |
| Location: Paderborn, Germany |
| Duration: 5 months |
| Tasks: Managing Customer Service in local branch, Financial Consulting for Clients |
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| Publications |
2019 | Co-Author |
| Book: „Insurance & Innovation 2019“ |
| Chapter: „Natural Language Processing für die Versicherungswirtschaft“ / „Natural Language Processing for the insurance industry“ |
| Authors: Prof. Dr. Torsten Rohlfs & Thorben Schlätzer |
| Link to Book: Coming out in May 2019 |
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| Top Projects |
| Deep Reinforcement Agent |
2019 | Deep Reinforcement Learning is a very sophisticated approach to teach Artificial Intelligence to do a job. For this project, I developed an agent to properly steer a drone to a set target. Link |
| Deep Text Classification |
2019 | Using a self-generated data set, I reached a 98 % accuracy for predicting a text class for specific abstracts. I used a deep neural network that I trained to perform this task. Link |
| Text Preprocessing Pipeline |
2019 | Based on my bachelor thesis' gained knowledge, I developed a way to automatically prepare text in a way, that it can be used for tasks like classification, automatic summarization or keyword extraction. Link |
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| If you want to see more, visit this link |
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| Top Skills |
| Insurance Knowledge |
| 3 years of studying have done their part. The knowledge about the insurance industry as well as the requirements for data have helped me to develop better solutions. |
| Data Skills |
| My skills in Machine Learning/Deep Learning and also Web Data Extraction help to gather, structure, and analyze data in great amounts. This increases value for a lot of use cases. |
| Programming Skills |
| I'm already programming for about 10 years now. The general understanding of software and the underlying architecture have now been professionalized by many projects and courses. |
| Creativity |
| I have noticed that working with data does not only require good mathematical skills, but also challenges you in your creativity. It is useful to be able to transfer problems of financial industries to software solutions. |
Feel free to ask anything. I'm looking forward to your message.
