Data Scientist

You will be part of a department that covers both the BI and AI needs of the company. This role combines the responsibilities of a Data Scientist and a BI Developer. You will be involved in the entire data lifecycle, from data collection (SQL) and advanced modelling (machine learning, Python) to data visualization for end users using Tableau.

As a Data Scientist, you will help us uncover valuable insights hidden within vast amounts of data and enable smarter decision-making to deliver even better products. Your primary focus will be on applying data mining techniques, performing statistical analyses and building high quality prediction systems integrated within our products.

The BI aspect of the role focuses on empowering the business with data-driven insights that support strategic decision-making and operational efficiency. We are looking for someone who is passionate about transforming data into actionable insights and thrives in a dynamic, collaborative environment.

• Additional annual leave days
• Day off on your birthday
• Additional health insurance and dental service coverage
• Multisport card
• Food Vouchers
• Employee assistance program
• Flexible working hours
• Remote work with casual visits in the office
• Attractive annual bonus
• Referral bonus
• Training and development opportunities

• Advanced knowledge: SQL, Python.
• Basic knowledge: Tableau/Power BI, Linux, version control system.
• Skilled in applying statistical analysis and basic machine learning methods to real-world business problems.
• Excellent analytical, organizational and problem-solving skills, capable of working independently with minimal supervision.
• Strong communication and interpersonal skills, fluent in English.
• Must be collaborative, curious, business-focused, resilient, adaptable and passionate about technology.

• Business communication: understand business requirements and translate them into effective technical solutions.
• Data engineering (SQL): collection of data from different data sources to use them in ML models/Tableau visualizations.
• ML model development (Python): develop, deploy and monitor ML models (recommendation engine, marketing intelligence etc.) to help business decision making.
• Data analytics (Tableau): build dashboards that end users can use to get quick insight into the data.
• Storytelling: explain complex statistical results into understandable insights that business users can use in their decision-making process.
• Curiosity and precision: identify unusual patterns in the data, in case of error collaborate with data engineering team to fix the issue.