Senior Data Scientist

About the Role

Key Responsibilities

• Deliver end-to-end data science projects, from framing the business problem and developing models to delivering actionable solutions that create measurable business value.
• Analyze complex datasets on products, channels, customers, and markets using machine learning, statistical modeling, and advanced data wrangling techniques to uncover opportunities and risks.
• Create compelling data visualizations and performance storylines that drive action, bringing complex data science insights to life for both technical and non-technical partners.
• Own and continuously improve global performance tracking processes, using data science to identify trends, optimize commercial strategies, and inform key business decisions.
• Collaborate across teams - including Global Commercial, Analytics & Insights, Data Platform, Data Science, and Digital Products - to ensure seamless integration of analytics solutions and alignment with broader business initiatives.
• Coach and mentor junior team members, share knowledge across the team, and stay updated with emerging data science techniques and technologies to improve impact.

Requirements

• Proven experience applying machine learning and data science techniques to solve complex business problems.
• Proficiency in SQL, Python (including data science libraries), and version control tools like GitHub.
• Solid skills in data wrangling, modeling, and data visualization with an ability to balance speed and quality in a fast-paced environment.
• Superb communication skills to present complex methods and findings clearly to both technical and non-technical audiences.

Nice to Have

• Previous experience with Machine Learning Attribution Models and Causal Inference.
• Experience or familiarity with Databricks, Agile Framework, Asset Bundles, MLOps Stacks, GitHub actions, and Generative AI.
• Demonstrated experience working with partners to identify high-value solutions and deliver actionable results.
• A collaborative, positive approach and experience coaching or mentoring junior data scientists.
• A passion for continuous learning, staying on top of the latest techniques and technologies, and sharing knowledge with your team.
• Previous experience in commercial analytics or the consumer goods industry.
• Bachelors, Master's or Ph.D. in Data Science, Computer Science, Engineering, Business Analytics or a related field.

Qualifications

• Bachelors, Master's or Ph.D. in Data Science, Computer Science, Engineering, Business Analytics or a related field (preferred).

Benefits & Perks

• Family Care Leave with enhanced paid leave options.
• Life and disability insurance coverage.
• Access to wellbeing initiatives and programs, including the Headspace App.
• Generous colleague discount from day 1.
• Bonus scheme based on reaching goals and eligibility.
• Hybrid working model with an average of 3 days per week in the office.
• Workplace flexibility and support for diverse life situations.