You will join the analytics team, a group of risk analysts/data scientists/data engineers/software engineers with a broad background in data science and risk modelling, to create and shape data and technology driven solutions across creditshelf’s various teams (Risk, Sales, Marketing, etc).
You will create, maintain and improve cutting edge models for credit risk, portfolio management, fraud prevention/detection, stress testing, etc.
As data scientist, your responsibility is the design, development and implementation of prediction models and deep learning algorithms and support the whole end-to-end development and implementation process.
You will advise in collaboration with the team on our data collection and storage.
You will educate and coach our teams to demonstrate the power of data-driven decision making to help build creditshelf as a data-driven company.
A degree in STEM, Finance or other fields with a strong quantitative focus.
A couple of years of work experience requiring data science skills.
You have proven project experience in applying ML on real world problems, ideally in the financial world.
You have programming skills in multiple languages, dynamically typed, and their libraries (such as Python, R, MatLab, pandas, sklearn, numpy, e1071, etc.).
You are able to visualise your work, e.g. using matplotlib, ggplot, Tableau or similar.
If you are not scared of statically typed languages as Java, Scala, C++ - this is a plus.
A high curiosity for SME lending and the financial sector.
Openness for working in a dynamic and agile start-up environment and a “why not?” attitude for challenges.
Familiarity with different databases, SQL, NoSQL, Knowledge Graph databases, and related technology in an AWS surrounding is a plus.
The chance to recreate the world of finance for the better!
True ownership of your projects – if you have an idea, we will let you shape it!
Real appreciation of your contribution – we believe in the value you create!
Continuous support of your development – We are experts in what we do and we want to share our knowledge!
Little perks for a nice workplace:
Quarterly Events Monthly Mystery Lunch Weekly Thirsty Thursday Daily Lunch Culture … and moreIf you are interested in gaining experience within an exciting and diversified field and in working in a dynamic and growing FinTech environment, don’t hesitate to send us your CV and a motivational letter.We look forward to getting to know you!
Data Scientist (m/f/d) at creditshelf (Frankfurt am Main, Deutschland)
Stack Overflow · 13.05.2019