What you'll do:

• Collaborate with product design and engineering teams to develop an understanding of needs.
• Research and devise innovative statistical models for data analysis and communicate findings to all stakeholders
• Enable smarter business processes by using analytics for meaningful insights
• Keep current with technical and industry developments
• Execute analytical experiments to help solve problems across various domains and industries
• Analyse data for trends and patterns, and interpret data with clear objectives in mind
• Implement analytical models in production by collaborating with software developers and machine-learning engineers

What makes you a great fit:

• Understanding of probability theory, distributions and statistical inference
• Regression analysis (linear, non-linear, multivariate)
• Time series analysis / forecasting
• Experience in Bayesian statistics, Hypothesis testing, Experimental design
• Understanding of overfitting, underfitting, and regularization techniques
• Supervised learning algorithms
  
• Unsupervised learning (clustering, dimensionality reduction)
• Feature engineering and selection
• Model evaluation and validation techniques
• Proficiency in Python or R and SQL for database querying
• Understanding of causal inference
• Understanding of adstock, decay, and saturation concepts
• Cloud computing platforms (e.g., AWS, GCP)