Data Analyst I

**About the Team**

ShopriteX was established to accelerate the use of data to improve customer experience and business operations. Our Agile way of working allows for flexibility to grasp new opportunities and quickly transform them into insights that will have a direct impact on strategic initiatives.

The Insights & Data Monetisation Tribe harnesses big data, technology and advanced analytics to derive revenue from customer insights. It is made up of three squads: Assortment & Customer Intelligence, Pricing & Promotions and Supplier Insights. Some highlights of the Tribe duties include developing customer centric analytics products and insights, building recommendation models to ensure we have the correct product offering, evaluating the end-to-end effectiveness of promotions to reduce sales dilutive promotions and identifying key value items driving brand price perception to maintain price leadership.

As a data analyst you must be curious, enjoy digging into data to unearth insights and be passionate about the value this can add. Willing to take initiative, expand on new responsibilities and empower yourself with new skills and techniques as you grow with the team. This is an exciting opportunity and will be a close and collaborative journey with the IDM Tribe to develop your technical skills and grow into an advanced analytics role.

**Role Purpose**

The purpose of the Data Analyst role is to leverage Shoprite's rich customer and transactional retail data assets to provide actionable trends and insights that enables business to make sound commercial decisions. The role works collaboratively in a cross-functional, agile team, executing a variety of complex data analytics projects, including modelling and framing of business scenarios to solve analytical problems, performing experimental design approaches to validate findings or test hypotheses, depicting and presenting the rationale of findings in easy-to-understand terms for business and providing consolidated business reports and metrics. The Data Analyst is a critical thinker who applies their technical, analytical and communication skills to infer meaning from data and translate these in a concise, cohesive and engaging story.

**Role Description**
- Query large data sets and develop data tables
- Transforming data science outputs into consumable business output Transforming data into a story and presenting findings to business partners
- Reworking data and performing data cleansing ensuring integrity and usability
- Capacity to foster a healthy, stimulating work environment that frequently harnesses teamwork
- Value measurements of products (products are pieces of work delivered to business)
- Use Alteryx & VBA (or similar tools) to provide insights (rework data, and build logic recommendation models etc)
- Build, update & maintain use case driven Tableau dashboards to answer business questions
- Interacting with stakeholder to determine requirements, value & how reports will be used
- Presenting methodologies to business partners for sign off

**Qualifications and experience**
- Degree or Diploma in Data Science, Computer Science, Information Technology, Information Systems or a related field

**Essential**
- 2 years experience using SQL
- Should be able to join different data sets, understand how to bring together data on different data grains.
- 2-4 years Advanced Excel (pivot table is, h/vlookups, Index Match)
- Have built a dashboard using form controls in Excel or used a visualisation tool like Tableau/PowerBI/Qlikview to build insightful dashboards

**Advantageous but not required**
- Alteryx / Knime (advantageous)
- Cloud Platform / AWS EMR (advantageous)
- AWS Athena or Zeppelin/Jupyter notebooks (advantageous)
- Strong proficiency in MS Word with an advanced level of Excel skill

**Desired**
- Knowledge of AWS cloud computing based solutions (Python / PySpark)
- Experience working in an agile environment
- Experience working with retailer specific data (e.g. brand, customer, shopper, category, sales, promotions, pricing, channel, POS, payment / tender, store, stock and supply chain data)
- Alteryx / Knime (advantageous)
- AWS Athena or Zeppelin/Jupyter notebooks (advantageous)

**Key competencies and work ethic**
- Strong analytical thinking skills and highly numerate - Able to collect, organise and assimilate disparate, multiple and complex pieces of data to draw sound conclusions and arrive at optimal solutions. Able to dig deep to reach the right metrics that can be optimised
- High level of self-motivation and drive to meet and exceed on goals and expectations. Able to work independently and use own initiative to deal with challenges across a range of problem-solving challenges as and when they arise
- Detailed, organised and quality focused - Has an affinity for detail, structure and efficiency, balancing planning and execution. Is diligent and vigilantly watches over tasks, processes, and outputs to ensure accuracy while independe