Assistant Manager Digital Analytics

PURPOSE:

An Assistant Manager Digital Analytics is a specialist who applies its expertise in generating actionable insights from data and answer key business questions. They focus on understanding, cleaning and analysing data from different data sources, generating impactful visualizations, automated reports and self-service dashboards.

Key Responsibilities: - Scope: Contribution to a specific analytic deliverables or services

Analytics:

• Undertakes analytical activities and delivers cross channel analysis outputs, in accordance with customer needs, ad hoc requests prioritization and conforming to agreed standards.
• Project and Program Management support in different analytics workstreams.

Data Modelling and Design:

• Applies data analysis, design, and modelling techniques to establish, modify or maintain a data structure and its associated components (entity descriptions, relationship descriptions, attribute definitions).

Data Visualization:

• Applies a of variety visualization techniques and designs the content and appearance of data visuals.
• Operationalizes and automates activities for efficient and timely production of data visuals.
• Selects appropriate visualization approach from a range of applicable options.
• Contributes to exploration and experimentation in data visualization.

Dashboard Development:

• From ideation to development and maintenance of dashboards, aligning on expectations, usability, data quality checks and problem solving.
• Support on sprints, planning and keeping track of each step of development.

Key Relationships:

• Cross channel sales teams
• COE Ecom/Retail/WHS
• Global Digital and Digital Analytics teams
• BUs, Brand and Markets
• Data & Analytics and Tech

Requirements, Education & Professional Experience:

• A degree in mathematics, economics, statistics, computer science or a similar quantitative field.
• First practical experience in data analytics, data modelling, or a similar function.
• Proficient spoken and written command of English.

Soft-Skills:

• Good communication skills, comfortable presenting complex topics to stakeholders at various organizational levels both in person and remotely
• Good presentation skills and story-telling

Hard-Skills:

• Experience in statistical modeling and data analysis experience (e.g. significance testing, regression modeling, sampling theory etc.) and knowledge of linear algebra, calculus, probability and statistics.
• Experience finding, cleaning, manipulating and transforming data to build reports, dashboards and / or data assets.
• Experience with SQL, NoSQL, Hadoop or other data querying languages.
• Good visualization skills e.g. Microstrategy, Power BI, matplotlib, Plotly or something similar