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Job Summary
Essential skills:Python – to create models
Modelling Experience
SQL - advanced
DAX
Power Query
Data science course or qualification
AI including ML
Microsoft 365 (Advanced Excel)
SAP
PowerBI
Experience in cloud platforms
REQUIREMENTS:
Matric / Grade 12 or equivalent (Mathematics strongly recommended)
Diploma or Degree in Data Analytics, Data Science, Computer Science, Information Systems, Statistics, Mathematics or Industrial Engineering (or equivalent)
Proficiency in SQL for data extraction and reporting (formal certification advantageous)
Industrial Engineering Qualification
Microsoft Power BI (DAX and Power Query / M), SQL (querying relational data sources), Issue-Based Information System (IBIS), SAP, Microsoft 365 (advanced Excel) and Microsoft Projects
SQL Certification
4 to 6 years in a data analyst or business intelligence role, ideally within an operational, logistics, manufacturing or mining environment
3 to 5 years building reports and dashboards in Microsoft Power BI, including hands-on SQL for data preparation
Exposure to business, asset or production data; experience with data modelling and data quality; and familiarity with Python for analytics is advantageous
Exposure in the use of Generative AI and Machine Learning
RESPONSIBILITIES
To extract and consolidate data from operational source systems (such as IBIS, SAP and other data sources) using tools such as SQL and Power Query
To keep up to date with bleeding edge technology such as generative AI and build tools intelligently while keeping compliance to data governance and privacy protocols
To deliver end-to-end reporting solutions, from problem definition and data acquisition through to data modelling, analysis and visualisation in Power BI
To identify operational efficiency, utilisation and cost-optimisation opportunities across the business using data and statistical analysis
To analyse and interpret operational data and translate findings into clear, actionable insights for decision-makers and through projects
To develop and maintain the reporting datasets and Power BI dashboards by sourcing, structuring and validating data for accuracy, relevance and completeness, and integrating it into the data model within agreed deadlines
To analyse fleet metrics such as but not limited to utilisation, productivity and associated data, identifying patterns and trends, and presenting insights and recommendations within agreed deadlines
To implement and maintain data quality controls by profiling data, defining validation rules and quality measures, and monitoring data integrity on an ongoing basis
To automate recurring and high-impact reports by standardising report definitions and building repeatable refresh and reporting structures, delivering within agreed deadlines
To review fleet data for risks, anomalies and opportunities, performing root-cause analysis and reporting insights and recommendations as required
To gather and prioritise data and reporting requirements in collaboration with stakeholders, and provide delivery feedback within agreed deadlines
To address data gaps by detecting inconsistencies and errors, applying data cleansing and validation processes, and reporting on data quality as required
MECS Africa
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