We work in a HYBRID STYLE of working with an unlimited home office, but twice a week we meet in the office (Bratislava or Košice) for meetings.
Key Responsibilities
• You take the end-to-end responsibility for strategically aligned data science projects, from taking stock of requirements and advising through to putting the solution into production
• You will be applying machine learning approaches to provide business insights for internal customers of the Deutsche Telekom group
• You will be responsible for selecting the right modelling approaches and advising the Data Scientist teams on the methodologies to apply
• You will prepare training & evaluation pipelines and apply state of the art Machine Learning approaches to improve processes in Finance (Controlling, Treasury, Accounting), Procurement, HR, and others
• You are responsible for upskilling Data Scientist teams and preparing adequate training materials
• You will be driving innovation by staying up to date with the latest advancements in time series research (e.g., forecasting, clustering, anomaly detection) and identifying their potential applications within our products and projects
• We create data-driven business solutions for our customers. You will be the one creating them and possibly deploying them to production, teaching your customers how to use them, and providing support/maintenance
• You will be responsible for the technical part in your time series projects designing & implementing prototypes of innovative applications in Python
• You will cooperate with the business side including your active contribution in customer workshops, meetings, and calls so the ability to explain technical points to business colleagues is a crucial part of this job, as is a consultant’s mindset
• You will participate in team brainstorming sessions, code reviews, and pair programming sessions
• Depending on the use case, you will have the opportunity to work with a variety of tools and technologies such as Docker, Kubernetes, FastAPI, Redis, Celery and ML frameworks like SKTime, Scikit-learn, Nixtla, Tensorflow or other relevant libraries.
• You will have the chance to identify use cases for automation and application of data science
The published salary is the minimum possible offer. The starting salary may be higher depending on the extent of fulfillment of the employee's requirements (education, language skills, required practice, personality assumptions and skills).