Join the best company providing AI & Data Science services (No. 1 according to Gartner Magic Quadrant for Data and Analytics Service Providers 2021). Design and build machine learning models for the largest companies and institutions in Europe. Grow your career with technology vendors such as AWS, Google, IBM, Microsoft and SAS.
Requirements:
- studies in the field of computer science, statistics, mathematics, econometrics or any related field – minimum 3rd year of Bachelor/engineer degree
- interest in machine learning and statistical models, some familiarity with theory behind various machine learning concepts
- availability of min. 30 hours a week
- basic knowledge of Jupyter, Python, SQL or other languages and tools will be an advantage
- Passion to grow and learn
- Team-player mindset
- Good level of English
Your responsibilities
- Supporting customers with your skills in model development, assessing their frameworks and practices, giving recommendations for enhancing business processes
- Working with clients throughout the whole project cycle (Business understanding, Data understanding, Modeling, Evaluation and Deployment)
- Cooperation with subject matter experts from risk advisory and technical consultants to jointly deliver high quality projects for the customers
What we offer
- 6-month paid internship, which will include work in project teams in the implementation of tasks for our clients
- contact with new technologies
- the prospect of permanent employment after the end of the internship
- the opportunity to cooperate with experts and establish valuable professional relationships
- nice working atmosphere and the opportunity to participate in corporate events
About the team
Data & AI Team focuses on the practical applications of data analytics and artificial intelligence. Broadly understood risk management is a key area of companies' activity, covering both well-known applications such as credit scoring, fraud analytics or market risk analytics, but also new areas such as deepfakes detection, cyber intrusion, climate risk analytics, dynamic risk scoring. We also deal with the most important areas determining the success of implementations, such as AI explainability or AI fairness, and we take part in discussions on the regulation of the AI market in the European Union.