Data Scientist

Company Overview

team.blue is a leading digital enabler for companies and entrepreneurs. It serves over 3.3 million customers in Europe and has more than 3,000 experts to support them. Its goal is to shape technology and to empower businesses with innovative digital services.

Key Responsibilities

• Understand the key business challenges and opportunities, and use data to develop solutions that align with strategic objectives.
• Collaborate with leadership to define the data science roadmap and priorities based on business needs and opportunities.
• Build, deploy, and maintain machine learning models to forecast trends, optimize processes, and drive business outcomes.
• Analyze large, complex datasets to extract actionable insights, and present findings to both technical and non-technical stakeholders.
• Advise, build and continuously improve the data science pipeline which best responds to the company's analytics needs.
• Work closely with business leaders, product teams, and engineers to ensure that data solutions meet business requirements.
• Stay up to date with the latest trends in data science, AI, and machine learning to continuously improve the team's capabilities.

Requirements

• Masters or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 5+ years of experience in data science, with a proven track record of solving complex business problems using data.
• Strong understanding of business operations and the ability to align data science projects with business objectives.
• Ability to translate technical insights into business recommendations and communicate with stakeholders at all levels.
• Strong analytical thinking with the ability to handle complex and unstructured data.

Technical Skills

• Proficiency in programming languages such as Python, R, or Scala.
• Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn).
• Experience with SQL and working with large data sets.
• Familiarity with cloud platforms (e.g., AWS, Azure) and big data tools (e.g., Hadoop, Spark).

Benefits

• Respect, openness, and trusted collaboration are core values.
• Commitment to caring for the environment and each other through ESG initiatives.