Commercial Data Analyst (12-month contract)Listing reference: woolw_000965
Listing status: Online
Apply by: 8 October 2024
Position summaryIndustry: Wholesale & Retail Trade
Job category: Other: FMCG, Retail, Wholesale and Supply Chain
Location: Cape Town
Contract: Fixed Term Contract
Remuneration: Market Related
EE position: No
IntroductionAssist the Senior Commercial Analyst in using mathematical models and predictive economic research to provide insights to guide strategic and tactical decision making within a competitive commercial context.
Perform evaluations, analysis and present reports in support of remaining competitive within the business environment:Define and research technology, competitors, market segments, and other key content areas.Develop and use statistical models for evaluating investment decisions, risk or opportunity areas, and determining financial returns.Evaluate profit plans, operating records, financial statements, competitive information and other relevant data to make recommendations to support commercial decision making.Communicate complex and often contentious matters to a wide range of audiences both verbally and in writing.Assist with Data & Analytics Use Case creation and evaluation:Understand the data landscape around profitability reporting including organisation and product taxonomy, hierarchies, source system landscape and data flows.Assist with Data & Analytics Use Case development and evaluation and consequent review to ensure delivery of benefits, aligned to financial principles that are consistent with Woolworths' accounting principles.Minimum RequirementsRelevant financial qualification – BCom, CA (SA), CIMA, CFA or equivalent experience required underpinned by strong capability in data analytics and quantitative analysis.
University degree in Business, Mathematics, Statistics, Economics, Industrial Engineering, Risk Management, or equivalent industry training and experience.
CA (SA): 2-3 years commercial experience (if CA, then post qualifying experience).
5 years experience of Financial Modelling with strong interpersonal skills, including being able to go beyond the numbers to generate hypotheses and make sound business recommendations. Knowledge of Financial tools.
Strong data leaning with experience in data mining and working with large databases.
Able to effectively use latest decision support technologies & tools.
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