Extract data, analyse that data and formulate reports and insights - as required.
Deliver buying performance reports with actionable insights - as required: periodic - daily, weekly, monthly, quarterly etc.
Produce meaningful KPI dashboards.
Support the team from a technical perspective in their understanding and use of data and analytics tools.
Data Analysts in the buying function portfolio would typically:
Produce/develop reports for buyers.
Analyse the reports for the buyers.
Provide business analysis support to buyers.
Advise buyers on range, supplier profitability/performance.
Do ad-hoc reports for buyers.
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Job Objectives
Develop and perform reporting and analysis on buying data.
Produce customised and new reports for buyers.
Draw information from data warehouse system.
Import into Exce.
Process data and produce reports - report on key metrics, analysing and interpreting trends and providing actionable insights based on the available analytics data
Identify problem areas/business needs in buying area.
Summarise critical issues.
Prepare info for supplier meetings.
Advise buyers on range, supplier profitability/performance.
Discuss reports with buyers.
Do ad-hoc reports for buyers.
Develop buying dashboard concepts.
Support the team in the development of various decision-making processes and/or identifying and optimising opportunities.
Identify the buyers' objectives and advise on suitable measurement strategies.
Benchmark performance and advise on key performance indicators.
Use methodical performance analysis to influence and support buying decision-making and strategies.
Source of support to the community using data and analytics.
Assist in educating stakeholders on the variations and benefits of data analysis and the importance of localised / category-based measurement & performance optimisation.
Collaborate with other data analyst capabilities in the organisation to participate in communities of good data analytics practice - both in BAU and project activities.
Collaborate with buying and other teams to enhance reporting and performance measurement.
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Qualifications
Working towards: Bachelor's Degree in Data Science, Computer Science, Mathematics, Statistics, Information Technology, Information Systems, or a related field.
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Experience
+1 years' experience in a Data Analyst or similar role, solving business and technology problems through applying data analysis techniques within a fast-paced environment - (essential).
Experience applying data mining, modelling and mathematical and/or statistical concepts and methodology to support strategic business objectives - (essential).
Experience in a retail, commercial or IT environment - (highly desired).
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Knowledge and Skills
Knowledge of data base integration systems.
Knowledge of SQL, Python, and data analysis toolkits.
Strong proficiency in MS Office 365 with advanced Excel skills
An An emerging data specialist with a passion for practicing the art of Data Analytics.
Analytical and highly numerate - Able to collect, organise and assimilate disparate and multiple pieces of data to draw sound conclusions and arrive at optimal solutions.
Technical aptitude with a passion and excitement for data, new technologies and solutions and its range of possibilities, applications, and value for the business.
Commercial awareness - Able to spot commercial opportunities in retail / buying data.
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 in areas of familiarity.
Detailed, organised and quality focused - Has an affinity for detail, structure and efficiency, balancing planning, and execution. Is diligent and vigilantly watches over work processes, tasks, and outputs to ensure accuracy while promptly escalating and correcting any quality concerns.
Good communication skills - Communicates well both verbally and in writing. Able to explain and simply technical concepts and confidently convey information to stakeholders. Able to compile well-developed and visual reports.
Team player and collaborative partner - Works effectively as part of a multi-disciplinary team. Is collaborative and able to build sound, professional relationships with business stakeholders.
Ability to work under pressure and under tight time constraints, efficiently prioritising workloads and managing time effectively in a high-volume, fast-moving environment.
Is curious and open to learning with a strong interest in data, discovery and trying new ideas. Curious about exploring and answering business analytics questions.
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