01Requirements
The ideal candidate is an experienced data scientist with strong machine learning expertise, business acumen, and the ability to independently deliver analytical solutions. You should be comfortable working with customer analytics, forecasting problems, cloud platforms, and modern data science tools.
- Commercial experience applying classical data science and machine learning models, including decision trees, ensemble-based models, and linear regression.
- Strong understanding of consumer analytics concepts and advanced forecasting techniques.
- Experience with hyperparameter tuning and model validation frameworks.
- Ability to gather business requirements, design technical solutions, process data, engineer features, and evaluate models.
- Experience supporting business teams through analytical insights and data-driven recommendations.
- Strong programming skills in Python and basic working knowledge of SQL.
- Familiarity with data science and machine learning libraries.
- Experience working with cloud computing platforms such as Databricks, GCP, or Azure.
- Strong analytical thinking and ability to solve complex business problems creatively.
- Good understanding of programming concepts and software development practices.
- Preferred: Knowledge of causal machine learning and advanced modeling approaches.
- Preferred: Experience working with big data environments and distributed computing.
- Preferred: Experience with forecasting projects, MLOps, object-oriented programming in Python, or additional languages such as R and Scala.
- Preferred: Experience with deep learning, reinforcement learning, or other advanced data science techniques.
Benefits:
- Fully remote work environment with flexibility regarding working hours.
- Stable full-time employment within an established global technology organization.
- Comprehensive onboarding program with dedicated support from day one.
- Opportunity to collaborate with experienced engineers, data scientists, and technology experts.
- Access to online learning platforms and continuous professional development resources.
- Technology certification programs and support for career advancement.
- Capability development programs, knowledge-sharing sessions, and community learning opportunities.
- Strong internal growth opportunities with career progression paths.
- Diverse, inclusive, and .
