Description & Requirements
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:
- Bachelor/engineer degree (preferred computer science, statistics, mathematics, econometrics, or any related field)
- 4+ years of professional experience in programming and solving business problems using advanced analytics and data science
- Understanding of machine learning and statistical models, some familiarity with theory behind various machine learning concepts
- Practical knowledge of Jupyter, Python and SQL or other languages and tools.
- Basic experience in one or more cloud environments (AWS, Azure, GCP, IBM)
- Passion to grow and learn
- Team-player mindset
- Good level of English
Your future role
- 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
- A clear career path and Career Coach, who will guide you through the organization and your opportunities
- Wide range of trainings and knowledge development opportunities, including financing of your certificates and workshops in a chosen career specialization
- A unique opportunity to develop the AI career with a great team of experienced peers and cooperation with Deloitte AI Institute
- Challenging tasks with the freedom of action in your field
- Friendly team atmosphere, flexible working set-up and excellent working conditions
About Deloitte
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.