1. Competitive compensation commensurate with role and skill set
2. A fast-paced, growth-oriented environment with the associated rewards
About Our Client
The company is a professional business services provider operating within the professional services industry. As a small-sized organisation, it is known for its innovative approach to delivering high-quality analytics and data-driven solutions.
Job Description
External Interfaces
Internal Interfaces * Vendors (if required)
* Contractors (if available)* Data & Analytics Leadership
* Global Data & Analytics team
* Other relevant teams of the organisation including Global Marketing, Merchandising, Global Technology, and Business UnitsJob Requirements Education
* Bachelor's degree in computer science, Information Management or related technical fieldsRelevant Experience
* 2 + years for Data Analyst
* Relevant working experience in a quantitative/applied analytics role
* Experience with programming and the ability to quickly pick up handling large data volumes with modern data processing tools, by using Spark / SQL / Python
The Successful Applicant
1. Clean and organize large datasets for analysis and visualization using statistical methods; verify and ensure accuracy, integrity, and consistency of data
2. Identifying trends and patterns in data and using this information to drive business decisions
3. Create the requirement artefacts, Functional specification document, use cases, requirement traceability matrix, business test cases and process mapping documents, user stories for analytics projects
4. Build highly impactful and intuitive dashboards that bring the underlying data to life through insights
5. Generate ad-hoc analysis for leadership to deliver relevant, action-oriented, and innovative recommendations
3. Functional Analytics (Retail Analytics, Supply Chain Analytics, Marketing Analytics, Customer Analytics, etc.)
4. Working understanding Statistical modelling using Analytical tools (Python, PySpark, R, etc.)
5. Enterprise reporting systems, relational (MySQL, Microsoft SQL Server, etc.), and non-relational (MongoDB, DynamoDB) database management systems
6. Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)
7. Cloud computing services in Azure/AWS/GCP for analytics