We are seeking a highly creative and motivated software engineer to support and accelerate research in the Data Mining Group at the Eindhoven University of Technology. The candidate will be working on two separate research projects: the Open Machine Learning (OpenML) project and the Next generation predictive analytics for data-driven banking and insurance (RATE Analytics).

OpenML.org is an open science platform for machine learning. It allows anyone to share machine learning datasets, algorithms, models, and experiments. Is has a web interface as well as APIs in Python, R, Java, .NET, and integrations in several open source machine learning libraries, such as scikit-learn, mlr, WEKA, and MOA. It is an open source project hosted on GitHub, with over 20 core developers from across Europe and the USA. You'll become a key part of this community, helping to further develop and maintain the platform. Ideally, you are well-versed in front- and backend web development (Python, Javascript,databases,...), but also software development in Python and possibly other languages. You will be working with many different machine learning libraries  (e.g. scikit-learn, Keras, TensorFlow,...) and implement algorithms to automate experimentation and model building. You will likely also be involved in ongoing research into Automatic Machine Learning (AutoML) and other topics. You are also expected (and welcome) to participate in hackathons, workshops, and tutorials.  This work is set in an very interactive environment, including the Eindhoven Data Mining Group, the OpenML team, and the AutoML community.

RATE Analytics in the joint NWO and industry funded project including collaboration of TU Eindhoven, Tilburg University, Rabobank and Achmea. It is led by prof. dr. Mykola Pechenizkiy (predictive analytics), prof. dr. Bas Werker (financial statistics and econometrics) and prof. dr. Jack van Wijk (visualization). The project includes two postdocs and two PhDs working full time on this project.

The overall goal of this project is to develop foundations and techniques for next generation big data analytics, facilitating the development of a wide range of applications in banking and insurance. including, but not limited to transactions and insurance fraud detection, loan default prediction, customer churn prediction, and data-driven product development.

We bring three major data-science expertise areas into this multidisciplinary project: predictive analytics, modern statistics, and visual analytics to develop novel approaches for analytics with an expert in the loop and the expert-algorithm interaction.

We are looking for candidates that meet the following requirements:

a solid background in Computer Science with specialization in software engineering, data science, data mining, machine learning, visual analytics, visualization or related areas

excellent programming skills. Experience with open source development is an asset;

Data Science software development skills (Python, R,...);

knowledge of machine learning/data mining techniques;

Web development skills (e.g. Flask, React,...);

excellent communication skills in spoken and written English;

capability and willingness to work both independently and in a team of data scientists and interact with domain experts; being highly motivated, rigorous, and disciplined;

creativity, free thinking, perseverance;

being enthusiastic about working on two different projects and changing use cases.

We offer:

A full time temporary appointment for a period of 3 years, with an intermediate evaluation after 9 months;

A gross salary of Euros 2640 - 4166 (scale 9 or 10 CAO Dutch Universities) according to your level of experience;

Tight collaboration of academia with industry with access to real data and domain expertise.

Strong collaboration ties with several research groups in Europe and world-wide.

Healthy travel funding for presenting your work at the leading data mining conferences.

Support for your personal development and career planning including courses, summer schools, conference visits etc.;

A broad package of fringe benefits, e.g. excellent technical infrastructure, child daycare and excellent sports facilities, extra holiday allowance (8%, May), and end-of-year bonus (8.3%, December).