Data Scientist

How about?

• Employment contract? Of course. With us you do not have to worry about stable employment.
• ‎Flexible working hours? Sounds great! We start working between 8 to 10.
• Friendly atmosphere at work? Yes! In PAYBACK, people are the most important asset‎.
• Benefits? We have them! Among other: corporate incentive program, sport card, private medical care.
• Convenient location? Sure! We invite you to our new office at Rondo Daszyńskiego, but we are currently also working remotely.
• Dress code? We definitely say no. There are no rigid dress code rules in our company, sneakers are more than welcome.
• Trainings? Of course. We provide training to develop hard and soft skills.
• Working in a hybrid model? Of course! You work with us 2 days a week from the office, 3 days a week from home.
• ‎Something is missing? Open communication is our priority, so dare to ask!‎

• You develop and build Data Products with a Modelling component at PAYBACK together with internal stakeholders.
• You work along the entire model life cycle guiding Data Products from conception to production.
• In a team structure you develop models that are productively deployed.
• You are responsible for the maintenance and the continuous improvement as well as for the monitoring of deployed models.
• You use efficiently the available MLOps and Cloud Infrastructure.
• Your goal is to improve the personalization of direct and digital Marketing campaigns, as well as PAYBACK’s own App.
• You work in close cooperation with IT and Business in a product centric way.

• Succesfully completed studies of Statistics, Mathematics, Computer Science or other related quantitative fields of study.
• Relevant knowledge in Data Science, Statistics, Machine Learning and Deep Learning methods.
• Used Python through-out the full model lifecycle from inception to monitoring.
• Willing to upskill to production-level Python programming.
• Experience with building REST APIs.
• For extra points: Knowledge of Docker and Microservices, familiarity with Kubernetes and / or experience with an MLOps framework (Kubeflow, Seldon, MLFlow, ...).
• For extra points: Cloud Experience (Vertex AI, Sagemaker, Azure ML).
• Ability to address, structure and analyze complex problems and questions.
• Strong communication skills, persuasiveness and proactivity.
• Proficient in English language.