The role involves applying advanced analytical techniques, machine learning, and statistical modelling to solve complex problems related to category growth, pricing & promotion, e-commerce analytics, and loyalty programs.

Roles & Responsibilities:

• Design and implement predictive and prescriptive analytics models to forecast sales trends, tailor customer experiences, anticipate customer attrition, and enhance strategies for product assortment, pricing, and promotions.
• Apply a wide range of advanced analytics techniques, including statistical modeling, machine learning (regression, clustering, decision trees), deep learning, and natural language processing.
• Utilize cloud-based tools like Microsoft Azure and Snowflake to efficiently access, process, and manage large datasets for analytical and modeling purposes.
• Collaborate with data engineering teams to build scalable data pipelines, ensuring clean and well-organized data for analysis and machine learning workflows.
• Interpret and analyze large, complex datasets to uncover key insights, patterns, and trends that influence strategic business decisions.
• Identify and define customer segments, enhance loyalty initiatives, and build data-driven marketing strategies through advanced analytical methods.
• Develop interactive dashboards and reporting tools using Power BI to monitor performance metrics and effectively communicate insights to stakeholders.
• Lead initiatives focused on innovation, including customer behavior modeling, store analytics, and personalized omni-channel engagement.
• Work cross-functionally with teams across marketing, commercial, and operations to translate business goals into actionable data solutions.
• Stay informed on the latest trends in data science and AI, and recommend new approaches or technologies that drive business innovation and operational efficiency.

Minimum Requirements:

• Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
• 3 - 4 years’ experience as a Data Science Analyst, with at least 1 year in Retail, FMCG, or e-commerce.
• Strong programming skills in SQL, Python, and/or R. Proficiency with ML frameworks like scikit-learn, TensorFlow, PyTorch.
• Solid understanding of statistical analysis, predictive modelling, and experimental design.
• Experience with Microsoft Azure or other cloud-native data architectures.
• Experience with data visualization tools such as Tableau, Power BI, or similar.