About the project

• We are seeking a highly skilled Data Scientist to join our analytics team. The ideal candidate will be responsible for designing and implementing advanced analytical models to solve complex business problems. This role involves working with large datasets, applying statistical and machine learning techniques, and communicating insights to stakeholders to drive data-driven decision-making.
• This role provides an exciting opportunity to work on cutting-edge data science projects and make a significant impact on business outcomes. If you are passionate about leveraging data to solve real-world problems, we encourage you to apply.
• MD rate: 160 - 200 EUR

Your responsibilities

• Analyze large and complex datasets to uncover actionable insights and trends.
• Develop and implement machine learning models and statistical algorithms to solve business challenges.
• Collaborate with cross-functional teams to understand business requirements and translate them into data science projects.
• Design and optimize predictive models and recommendation systems.
• Visualize data insights and present findings to stakeholders through dashboards and reports.
• Work with data engineers to ensure data availability, quality, and integrity for analysis.
• Conduct A/B testing and experiments to validate hypotheses and measure the impact of changes.
• Stay updated with the latest advancements in data science and machine learning technologies.

Our requirements

• 3+ years of experience in data science or a related field.
• Proficiency in programming languages such as Python or R for data analysis and modeling.
• Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with SQL for querying and managing large datasets.
• Familiarity with data visualization tools like Power BI, Tableau, or Matplotlib.
• Knowledge of statistical analysis and hypothesis testing.
• Experience with big data platforms (e.g., Spark, Hadoop, Databricks).
• Strong problem-solving skills and ability to work in a fast-paced environment.

Optional

• Experience with cloud platforms like AWS, Azure, or Google Cloud for data science workflows.
• Knowledge of natural language processing (NLP) and computer vision.
• Familiarity with data engineering tools for ETL and pipeline automation.
• Experience with deep learning frameworks like Keras or FastAI.
• Understanding of MLOps for deploying and monitoring machine learning models.
• Certification in data science or machine learning (e.g., AWS Certified Machine Learning – Specialty).
• Exposure to Agile/Scrum methodologies.

Technologies we use

This is how we work on a project

• Continuous Deployment

• Continuous Integration

• functional tests