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siphiwe sebola

@siphiwesebola

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Data Analyst turning sales data into forecasts, dashboards, and revenue insights.

South Africa

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What I'm looking for

I’m looking for a role where I can build predictive models, automate reporting, and develop BI dashboards that support revenue growth and smarter operations—using Python, SQL, and Power BI in a team that values data-driven decision-making.

I’m a data analyst with 4+ years of experience applying sales analytics to forecasting, BI dashboarding, and predictive modelling. I enjoy turning raw, messy data into clear insights that teams can use to improve revenue performance and operational decisions.

At Mediamark, I designed predictive models using macroeconomic variables to forecast radio and TV revenue growth and support annual sales budget planning. I also built weekly revenue forecasting using historical sales revenue to model daily growth, achieving 95% accuracy on new, unseen data.

I focus on actionable analytics, from Market Basket Analysis using association rule learning to identify commonly purchased items, to improving how Non-Traded Revenue is calculated and tracked. I’ve also created new revenue reporting templates for each financial year and contributed to R&D of new products.

Currently completing an MSc in Data Science at the University of the Witwatersrand (Wits), I’m strengthening my technical depth in Python, SQL, Power BI, advanced Excel, and machine learning. I’m especially passionate about automating reporting and building data-driven workflows that make decision-making faster and more reliable.

Experience

Work history, roles, and key accomplishments

Current

Junior Data Analyst (Sales)

Current

Mediamark

Apr 2022 - Present (4 years 4 months)

Designed a predictive model using macroeconomic data to forecast radio and TV revenue growth, supporting sales budget planning for the new financial year. Built daily-to-weekly revenue forecasting models and conducted market basket analysis using association rule learning to support advertising strategies, while improving revenue reporting templates and non-traded revenue tracking.

predictive modeling Revenue Forecasting Macroeconomic Models Basket Analysis Association Rule Learning Sales Planning Non Traded Revenue Tracking Revenue Reporting R&D

Education

Degrees, certifications, and relevant coursework

University of the Witwatersrand (Wits)

Master of Science, Data Science

2025 -

Activities and societies: Key courses: Data Visualisation and Exploration; Statistical Foundations; Data Privacy and Ethics; Adaptive Computation and Machine Learning; Research Methods & Capstone; Artificial Intelligence; Mathematical Foundations.

Currently completing an MSc in Data Science at Wits with coursework spanning data visualisation, statistical foundations, AI, machine learning, and research methods, including a capstone project.

Nelson Mandela University

Bachelor of Science (Honours), Mathematical Statistics

Grade: 72%

Activities and societies: Honours project: estimation of transition probabilities (credit rating of companies); semester essay on South African financial instruments (bonds and shares).

Completed a BSc Honours in Mathematical Statistics, covering actuarial statistics, quantitative data analysis, multivariate methods, and a honours project on credit-rating transition probabilities.

University of Limpopo

Bachelor of Science, Mathematical Sciences

Grade: 65%

Activities and societies: Final-year focus included applied mathematics and statistics; minor courses: pure mathematics and computer sciences.

Graduated with a BSc in Mathematical Sciences, focusing on applied mathematics and statistics, with additional study in pure mathematics and computer sciences.