Data Scientist (m/f) - Berlin
- Berlin, Germany
Spotcap is a leading global fintech company operating in the trillion dollar online lending space. We are driven by the mission to empower SMEs with tailored finance, allowing them to focus on what really matters – their business. Spotcap operates in five countries and is headquartered in Berlin, Germany, with a local presence in the UK, the Netherlands, Spain, Australia and New Zealand. We are growing rapidly!
We are an international team of finance, engineering, marcomms and business professionals from more than 25 countries. Our most important asset are the masterminds behind Spotcap - our people. We are always looking for like-minded people who want to join us in empowering SMEs and evolving the finance industry.
We’re looking for a Data Scientist with proven experience of conceptualizing, building and deploying data science & machine learning solutions. You will work closely together with the Underwriting, Product and IT departments to conduct research, build prototypes, discover ways to improve our product offering, make better risk assessment and deliver scalable data driven tools.
In this role you will…
- Develop systems and practices that enables Spotcap to leverage cutting edge data mining and machine learning techniques.
- Work on improving Spotcap’s credit scoring algorithms based on traditional, non-traditional as well as text data for various financial products.
- Conduct research and build prototypes of data science solutions that aim at increasing the level of Underwriting automation.
- Drive data science initiatives in cooperation with the Underwriting team in order to generate expert knowledge and theoretical foundations for the next generation of credit scoring models.
- Help to establish efficient, automated processes for models development and validation.
- Be responsible for the implementation and continuous development of data science best-practices within the company.
Working at Spotcap means you will benefit from the following:
- Be part of a dynamic, driven and international team of more than 120 employees from 25 countries, with diverse backgrounds, based in our offices in the heart of Berlin.
- Strong career progression and the opportunity to grow with the business.
- A startup atmosphere in an established company environment with flat hierarchies - meaning you’ll be expected, and encouraged, to contribute your ideas.
- Training and development budgets which can be used for conferences, attending personal training and development courses to ensure continuous growth and development.
- A great company culture with regular social activities, tech talks and health and fitness initiatives.
- A collaborative working culture with regular brainstorms, stand-ups and inter-departmental gatherings across two continents.
- Choose your own device: the option to choose between a high-end Dell or Mac Notebook.
- Fresh fruit, drinks, cereals, and regular team breakfasts.
- Relocation support services.
Our ideal candidate...
- Has a BSc or MSc in an applied quantitative discipline e.g., Machine Learning, Artificial Intelligence, Data Science, Computer Science, Mathematics or Statistics.
- Is a team player and an intellectually curious self-starter.
- Is fluent in R and R Markdown. Has very good knowledge of the tidyverse libraries: dplyr, ggplot2, purrrr, tidyr as well as the newest machine learning stack such as: caret, resamples & recipes.
- Has practical knowledge in applying data science & machine learning techniques and can demonstrate experience in prototyping and productionizing data driven products.
- Has a proven track record of working in a dynamic work environment in a cross-functional team.
- Is able to communicate complex data solutions across the company - you can articulate experiment goals and methodologies clearly, and communicate insights in an easily accessible way to the team.
- (A plus) has experience working in the Financial industry, especially performing statistical modelling and credit scoring on different financial products such as: loans, credit lines, cash advances etc. (consumer or business products).