ML Engineer

Responsibilities

• check_circle Develop, implement and standardize Marketing Science solutions in proofs-of-concept and prototypes
• check_circle Continuously improve the efficiency of our Marketing Science products (e.g. ensure quality by adherence to coding guidelines, documentation and reproducibility)
• check_circle Optimize our Marketing Science models using code optimization, high-performance computing and real-time techniques
• check_circle Build analytical pipelines at scale using cloud services, containerized applications and distributed systems
• check_circle Identify best practices and create continuous improvement of tools and methods
• check_circle Collaborate closely with Product Owners, Modelers, Marketing Scientists and Front-End Engineers

Basic qualifications

• Bachelor or Master degree that reflects strong statistical/mathematical/computer science skills
• Strong expertise in Python - at least 3 years of development
• Understanding of R
• Experience in (predictive) statistical modeling and causal inference
• Ability to manage code deployments (experience with GIT)
• Basic understanding of Dockerization – building and managing docker images
• Experience with creating, managing and/or maintaining code documentation
• Solid skills concerning performance optimization and scalability (e.g., parallelization, code optimization, functions as a service)
• Experience with Cloud services such as Azure or AWS
• Ability to present and explain complex concepts to less experienced colleagues
• Familiarity of Kubernetes and Airflow is a plus

Benefits

• check_circle Flexible working environment
• check_circle Volunteer time off
• check_circle LinkedIn Learning
• check_circle Employee-Assistance-Program (EAP)

About the company