BI Analyst at Nedbank

Job Purpose

  • To determine tactical and operational business insights through analysing business processes, analysing data flows, defining measurement goals and storyboarding.

Job Responsibilities

  • Provide input into the business and enterprise BI requirements and then conduct research to understand industry best practice for value and insight's by applying advance analytics.
  • Produce the high quality, insights outputs including dashboards, reports and analytical solutions that support strategic decision making.
  • Translate complex data into clear, actionable insights through effective data storytelling and visualisation
  • Design and maintain governed semantic data models to enable scalable self-service analytics
  • Enable business users to independently access, interpret and use data effectively
  • Drive adoption of self-service BI through documentation, best practices and stakeholder support
  • Provide input into data architecture to ensure solutions are scalable and fit-for-purpose for analytics
  • Oversee the development of the solution by collaboration with BI Developers, Architects, modellers and business in accordance with the requirements and obtain SAF approval where necessary
  • Build collaborative cross functional relationships by assisting clients with resolutions of technical issues enterprise wide
  • Ensure work is completed asper the agreed SLA and OLA 's
  • Gather and document business requirements by facilitating information gathering sessions with the customer
  • Produce a conceptual and a logical model and dataflow diagram of the business processes for enterprise processes
  • Perform data mining techniques, to understand the attributes needed to obtain the measurement goals.
  • Create data mapping document to relate the data to the business requirements
  • Prototype the feasibility of the solution to guide business on the requirements
  • Ensure quality of output and alignment to requirements by conducting / coordinating unit; integration and user acceptance testing
  • Ensure compliance by adherence to Enterprise data standards; policies and procedures throughout the development lifecycle
  • Support the achievement of the business strategy; objectives and values by reviewing Nedbank and Business Unit
  • Share knowledge and industry trends with team and stakeholders during formal and informal interaction
  • Obtain buy-in for developing new and/or enhanced processes that will improve the functioning of stakeholders' businesses by highlighting benefits in support of the implementation of recommendations
  • Identify opportunities to leverage AI and advanced analytics to enhance insights
  • Apply AI-enabled tools and techniques (e.g. predictive analytics, anomaly detection, automation of insights)
  • Partner with analytics and engineering teams to support implementation of AI-driven use cases

Essential Qualifications - NQF Level

  • Advanced Diplomas/National 1st Degrees

Essential Certifications

  • Microsoft Certified Solutions Expert (MCSE): Business Intelligence
  • Microsoft Fabric Certification
    Certification in a specific BI Tool (e.g. Power BI

Preferred Certifications

  • Cloud (Azure, AWS), DEVOPS or Data engineering certification. Any Data Science certification will be an added advantage, Coursera, Udemy, SAS Data Scientist certification, Microsoft Data Scientist.

Minimum Experience Level

  • 7 years’ plus experience
  • Deep knowledge of machine learning, statistics, optimization or related field.
  • Experience with R, Python, Matlab is required, programming in C, C++, Java.
  • Experience working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
  • Excellent written and verbal communication skills along with strong desire to work in cross functional teams.
  • Attitude to thrive in a fun, fast-paced start-up like environment

Technical / Professional Knowledge

  • BI Tools (Advanced)
  • Managing business Meta Data advanced
  • DAX understanding intermediate
  • Data Virtualization understanding advanced
  • Data Visualization design and build advanced
  • Design Thinking advanced
  • Database Query advanced
  • Business writing skills (intermediate)
  • Data analysis Advanced
  • Research methodology advanced
  • Data Modelling - intermediate
  • Data Ethics basic
  • Data mining intermediate
  • Data profiling - intermediate
  • Data story telling -advanced
  • Business analysis methodology intermediate
  • Domain knowledge advanced

Behavioural Competencies

  • Applied Learning
  • Building Partnerships
  • Building Customer Relationships
  • Quality Orientation
  • Execution
  • Technical/Professional Knowledge and Skills
  • Influencing
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