Data Scientist

BizAway; Barcelona; Híbrido; EUR 40.000 - 60.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Attractive salary and equity in the company

Flexible working policy

Collaboration in a multicultural environment

Free coffee and beers

Descripción de la vacante

BizAway in Barcelona seeks a skilled professional to design and improve analytical solutions in a collaborative, hybrid work environment. You will be involved in translating data insights across various business functions in the travel industry.

The ideal candidate will have strong Python or R skills, experience in machine learning, and a relevant Bachelor's degree. Perks include an attractive salary and equity in the company.

Formación

• Experience in a Tech Company.
• Demonstrated experience with Python or R for data analysis and modeling.
• Knowledge of core machine learning concepts and libraries.
• Experience with BI Data Visualization tools.

Responsabilidades

• Design, build, and improve analytical and predictive solutions.
• Translate travel industry data into actionable insights.
• Engage with stakeholders to define KPIs and metrics.
• Contribute to data modeling and operationalize data science use cases.

Conocimientos

Python

R

Machine Learning

Data Visualization (Qlik)

Data Analysis

Strong Communication Skills

Teamwork

English Proficiency (B2)

Educación

Bachelor's degree in Statistics, Computer Science, Mathematics, Engineering, Economics or related field

Herramientas

Pandas

Scikit-learn

AWS

GCP

Azure

Descripción del empleo

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

Our offer

• Contract type: Permanent
• Working hours: Full‑time – 40h/week, from Monday to Friday
• Hybrid setting, flexible working policy, and great offices in Europe
• Salary: Attractive compensation, including equity in the company
• Equity in the company (stock options plan)
• A seat on a scale‑up with skyrocketing growth
• Development of your entrepreneurial spirit, having the chance to implement real‑impact business decision
• Multicultural and international team
• Collaborative and smart environment to work and learn
• Free coffee to kick‑start your day and free beers to celebrate together

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