Data Scientist

We are looking for

We are looking for a driven and enthusiastic Data Scientist (m/w/d) , who desires to contribute to the growth and success of our Data & Analytics Team.

Your role in BizAway

• You design, build, and improve analytical and predictive solutions, from statistical models to reporting and dashboards, turning findings into clear, actionable insights through charts, graphs, and dashboards.
• You learn all aspects of the travel industry from Finance, Products, Sales, and Service/Operations perspectives, translating data into actionable insights and verifiable reporting, and identifying opportunities where machine learning or automation can add value.
• By developing domain expertise in our industry, you engage with Business and Strategy stakeholders to help define KPIs and metrics, including how data will be captured, shared, modeled, and leveraged across our departments.
• You contribute to building the foundations of a comprehensive source of truth through data modeling, and you help prototype and operationalize data science use cases (e.g., forecasting, segmentation, recommendation).

Your basic qualifications

• Previously worked in a Tech Company
• Demonstrated experience with Python (or R) for data analysis and modeling
• Working knowledge of core machine learning concepts and common libraries (e.g., pandas, scikit-learn)
• Demonstrated experience with BI Data Visualization tools (Qlik preferred)
• Data analysis, presentation, and visualization experience
• Strong communication skills required
• Ability to work alone or in a team as required
• Bachelor's degree in Statistics, Computer Science, Mathematics, Engineering, Economics, or a related field is preferred
• English proficiency (written and spoken, level B2)

We are also interested in 

• Exposure to ML deployment, MLOps, or cloud platforms (AWS, GCP, Azure)
• Familiarity with generative AI / LLMs and their applied use cases
• Experience working with large or unstructured datasets

BizAway avoids any discrimination based on age, gender, sexual orientation, health status, nationality, political opinions, and religious beliefs in all decisions affecting personnel selection.