Senior Data Scientist

About the role

We are looking for a Senior Data Scientist to develop and deploy advanced analytics and AI solutions that drive business impact in the Consumer Insights and Analytics team. As a strategic partner to Marketing and Sales, the role requires a strong analytical mindset, expertise in building machine learning models, optimizing performance, and integrating cutting‑edge technologies to enhance decision‑making and automation.

Key responsibilities

• Develop and implement data science solutions to drive data‑driven decision‑making and support Consumer Insights & Analytics priorities.
• Analyze large, complex datasets using Databricks, Azure ML, Apache Spark and create statistical and machine learning models.
• Design deep learning and natural language processing models for complex business data.
• Monitor, evaluate and refine deployed models to maintain accuracy over time.
• Research and evaluate AI technologies to select optimal tools and platforms.
• Integrate latest data science innovations into product solutions to enhance analytical and automation capabilities.
• Collaborate with cross‑functional teams on omnichannel analytical projects.
• Build, maintain and improve analytics tools to accelerate speed to value.

Required profile

• Bachelor’s, Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Physics, Operations Research, Statistics or a related field.
• 5+ years of experience as a Data Scientist, Machine Learning Engineer or Applied Scientist, with focus on computer vision, NLP or data synthesis.
• Proven experience developing and deploying advanced analytical models and algorithms.
• Hands‑on programming in Python and R and experience with big‑data platforms such as Databricks, Snowflake, AWS, Azure ML, BigQuery.
• Experience transforming raw data into features, handling missing data, scaling, encoding categorical variables and dimensionality reduction.
• Experience designing and analyzing A/B tests and applying causal inference techniques.

Required skills

• Python
• R
• Databricks
• Snowflake
• AWS
• Azure ML
• BigQuery
• Apache Spark
• Power BI
• Tableau
• Amazon Marketing Cloud (AMC)
• Deep learning and natural language processing