Data Scientist

Quick Facts

• Role: Data Scientist

Description

As a Data Scientist, you will work with stakeholders across the business to design and deliver AI-powered solutions to meaningful problems. You will bridge technical possibility and business impact by developing and deploying machine learning and NLP models, including work with unstructured data. The role focuses on making AI practical, scalable, and useful.

Responsibilities

• Collaborate with business and tech teams to translate ideas into data- and AI-driven solutions

• Develop and deploy machine learning and NLP models using modern tools and methods

• Prepare structured and unstructured data for analysis and modeling

• Create visual and analytical outputs that support decision-making and communicate compelling data stories

• Contribute to internal initiatives to improve data infrastructure, tools, and methods

• Work in cross-functional, agile teams and keep stakeholders informed

Requirements

• C1+ fluent English

• Master’s degree or higher in a quantitative or technical field (e.g., Mathematics, Informatics, Natural Sciences, Engineering)

• Strong hands-on programming experience; knowledge of Python and Kubernetes (K8s) is a plus

• Experience with NLP tasks and unstructured data

• Familiarity with cloud platforms and tools for scalable model deployment (e.g., MLOps, Docker, Git)

• Strong analytical and conceptual skills with a structured approach to problem-solving

• Experience in high-performance, cross-functional teams and fast-paced project environments

• Ability to distill complexity and clearly communicate insights to both technical and non-technical audiences

• Comfortable working at the interface of business, data, and technology

• Proactive mindset with ownership from idea to implementation

Benefits

• Medical package, sports card, and sports sections

• Flexible working hours, confidential employee assistant program, and possibility of remote working

• Workshops, training courses, hackathons and meetups, digital learning platforms, and language courses

• Participation in CSR activities

• Team-building activities (e.g., bike races, soccer matches, film marathons)

• Diverse and inclusive environment that values qualifications, experience, and mindset