Senior Data Analyst (Retail Stores)
Progressive Edge
CapeTown, South Africa
2d ago
source : Executive Placements

Role Purpose

The purpose of this role is to create opportunities by leveraging the companys vast operational data. Using this data with predictive modelling you will have a direct impact on shaping tactical and strategic initiatives that drive our customer centric in-store experiences.

Data optimisation is all about integrating data with various in-store processes and financial models to enhance or create new opportunities.

This role monitors the end-to-end data pipeline to build data insights from multiple sources and tracks performance trends of various store activities, campaigns and / or operational changes by using the latest data insights.

This role provides concrete inputs that guide the team to either enhance, slow down or stop activities based on the trajectory of data findings and forecasts.

If you are an in-store, retail data fundi and feel passionate about customer centric opportunities and solutions, then we would like to hear from you, to discuss how you can take the lead in optimising available data.

Role Description

This role takes a hands-on approach to examining internal and external data to help improve revenue generation, reduce costs and enhance operational performance through data analysis, and where appropriate, supporting the data mining team in the creation of sophisticated algorithms or models.

This role is essential to support our in-store opportunities by increasing the level of data science applied to its business practices and customer experiences.

Key performance areas (1-5) :

  • Best practice research and adoption : in-store retail operations data mining and analysis.
  • Build an understanding of the companys data landscape, particularly as it pertains to the in-store retails operations context.
  • Participate in defining business problems with appropriate questions and by proposing a specific analysis approach (full data pipeline).
  • Apply sound data methods, integration and programming. Apply deeper data exploration and correlation analysis including building and deploying data models.
  • Participate in identifying and adopting appropriate technology.
  • Best practice research and adoption : in-store retail operations data mining and analysis.

  • As a subject matter expert, demonstrate a deep understanding of in-store retail operations and associated operational processes, products and pricing strategies.
  • Become an expert in identifying clear and accurate data points that enable proactive data analytics that support operational analysis and planning inputs.
  • Understand the business requirements including channel, segment and local sales performance - example : building a base of successful sales campaigns that can be replicated in similar formats and contexts in future.
  • Use the data and operational analysis inputs to build short- and longer-term planning roadmaps to prepare business stakeholders and stores for any changes or new ways of working.
  • Work with the local teams to obtain input, and support the local teams with urgent data insights to support successful operational execution / to achieve targets.
  • Work with business counterparts on operational readiness activities to ensure that necessary training and procedure updates have occurred.
  • Monitor all planning and execution activities - provide performance reports and input to reports and presentations that communicate the analysis undertaken, planning activities derived from the analysis, costing models applied and outcome of execution.
  • Work cross-functionally and actively participate in open and honest team discussions.
  • Maintain alignment across the team during analysis, planning and execution.
  • Monitor and assess competitors activity in data mining particularly as it relates to data analysis.
  • Monitor and assess global best practices in data mining particularly as it relates to data analysis.
  • Build an understanding of companys data landscape, particularly as it pertains to in-store retail operational data.

  • Spend time in stores to appreciate the nature of process flows and a first hand account of whats working and could potentially be improved.
  • Investigate, identify and categorise all data sources with particular attention to data that relates to or could relate to customer data and / or potentially apply to in-store retail operations context within the larger data pipeline.
  • Evaluate the customer data landscape in terms of opportunities to unlock value by taking a data mining approach.
  • Put in place a process to maintain the evolving data landscape.
  • Participate in defining business problems with appropriate questions and by proposing a specific analysis approach (full data pipeline)

  • Identify the primary in-store retail operations drivers and the appropriate analysis approach to categorise, define, dissect and interpret them.
  • Applications could include areas that hold a specific relationship with the in-store retail operations context : Workforce Management data, Supply chain analytics, Customer trends, behaviours and preferences, Marketing mix analytics, Price optimisation, Product recommendation, Fraud detection and prevention.

  • Work with the analysts applied statistics to explore the data and create and initial understanding of the problem and the data available to answer it.
  • Apply sound data methods, integration and programming. Apply deeper data exploration and correlation analysis including building and deploying data models.

  • Adhere to internal documentation, processes, protocols and standards.
  • Drive continuous improvement within team and workshop solutions to existing processes and challenges.
  • Apply sound data administration and analysis to ensure the quality and thoroughness of data.
  • Write business requirements / modifications to transform and data into common formats.
  • Write business requirements / modifications to create common report and graphical formats.
  • Prepare, publish and provide commentary for standing reports and dashboards on time against daily, weekly, monthly and annual deadlines.
  • Evaluate / investigate the quality / integrity / trend of data based on historical trends and industry norms.
  • Where appropriate manipulate data independently and present findings to the business
  • Work with the business to identify and prepare data for data mining or creating statistical models
  • Assist the business with putting in place reporting and analysis to monitor model performance
  • Communicate / Conceptualize and interpret the data status and issues to internal teams.
  • Ensure stability of the existing systems environment by implementing solutions and data models that do not compromise operational stability - use data to determine or identify potential conflicts.
  • Participate in post implementation reviews using data to inform the discussion
  • Participate in identifying and adopting appropriate technology

  • Work closely with solution architects, systems analysts and project managers in the design of solutions, data orientated opportunities etc.
  • Together with the data mining team engage the most appropriate stakeholders in the business and IT to obtain input and agreement on alternatives that are presented.
  • Provide insights and recommendations.
  • Qualifications and experience :

  • Degree or diploma in commerce, information or computer science discipline or equivalent - (preferred) but not essential if you have the right track record of delivery : specifically in the area of in-store retail operations orientated, full pipeline data analytics.
  • Ideally a minimum of 3-5 years experience in data and analytics in the FMCG Retail environment with great practical experiences and exposures in all facets of retail ideally in a fast paced and evolving environment.
  • Must be operationally equipped and understand the immediate practical data inputs that make up a sound data framework in this retail context - (essential)

  • Solid Advanced Microsoft Suite with Excel (advanced) - (essential)
  • Report writing skills in Tableau software or similar - (essential)
  • Strong understanding of data mining models, structures, theories, principles and practices
  • Knowledge of Business Intelligence and Data Warehousing - (essential)
  • AWS / cloud - (preferred)
  • Knowledge of legislation relevant to the collection, storage and exploitation of customer data - (essential)
  • Knowledge of data structures relevant to both operational and business intelligence systems - (essential)
  • Skill in using the open-source statistical package R, Python or similar - (essential)
  • Skills in using SQL in the data mining process, particularly for data preparation - (essential)
  • Presentation skills using Microsoft Office 365 powerpoint - (essential)
  • Google (Gmail, sheets, docs, slides etc.) - (preferred)
  • Key competencies and work ethic :

  • Self-motivated and driven with strong integrity - take accountability for actions and mistakes.
  • Can do attitude and Inspirational teamwork - a positive team member / planning lead who serves the team and shows an appreciation for a happy team environment, ability to coach and mentor others.
  • A passion for retail (FMCG) - sound channel and customer knowledge & understanding to develop effective in-store retail operations analysis.
  • Amazing flair for in-store retail analytics - generating options / alternatives, creating plans and making relevant connections to performance and commercial impacts.
  • Applying expertise and technology - delivering results and meeting customer expectations
  • Retail orientated Financial acumen - Cost modelling, process, system and reporting activities as required.
  • Strong relationships - including interpersonal skills and EQ at all levels, with all stakeholders. Build relationships both internally and externally.
  • Open, honest and direct, is comfortable in giving and receiving constructive feedback. Think and act independently as well as collaboratively.

  • Good balance between strategic and tactical mindset - able to research and integrate new options with immediate and longer term business benefit but also jump into operational mode where urgent and immediate activities take priority in the day-to-day practical context.
  • Operational efficiency - able to spread themselves across multiple tasks simultaneously by working smartly, efficiently and effectively.
  • Diligently staying on top of the details and understanding how they fit into the big picture. Process driven and methodical.

  • Time management - ability to prioritise a high volume of projects simultaneously in a fast-paced unpredictable environment.
  • Identify the urgent & important tasks and priorities to ensure delivery to client and other stakeholders.

  • Strong project / planning management - planning, and organization skills, including the ability to handle multiple projects simultaneously in a fast-paced environment.
  • Strong integrator - proven ability lead and drive cross functional work teams and projects.

  • Practical solution-orientated - thinks outside of the box. Sound judgment, quick decision-making and the ability to generate both short- and long-term solutions that serve the flow of work and deadlines.
  • Exceptional communication - approachable, adopts a range of influencing and negotiation styles to facilitate and deal with challenges internally and externally.
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