Head: Data Analytics and Insights at Nedbank

Job Purpose

• Responsible for the provision of end-to-end data requirements (sourcing, collation, analytics, modelling, visualisation, and storytelling) and to design, prototype, and build next-generation analytics and services by applying strong expertise in machine learning, data mining and information retrieval to enable data led decision making across Product, TS and CIB

Job Responsibilities

• Conducts advanced statistical analysis and develop best-in-class statistical models and algorithms.
• Develop complex models and algorithms that drive innovation throughout the business.
• Provide actionable insights, identify trends, and measure performance.
• Apply advanced analytical techniques such as machine learning and artificial intelligence in order to derive business value.
• Conduct data discovery for inclusion in models and collaborate with key stakeholders to grow business acumen and intellectual property.
• Understand business problems and designs end-to-end analytics use cases.
• Work with large data sets, simulation/ optimisation and distributed computing tools.
• Implements more advanced algorithms, e.g., complex descriptive.
• Understand current state of analytics more broadly and apply techniques from across industries.
• Oversee the implementation of operationalised machine learning and advanced algorithms.
• Monitor and continuously improve deployed models.
• Implement design of experiments and hypothesis testing.
• Design data visualisation for best fit and communication to business.
• Support the achievement of the business strategy, objectives and values.
• Contribute to the Nedbank Culture building initiatives (e.g. staff surveys etc.).
• Seek opportunities to improve business processes, models and systems through agile thinking.
• Provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders
• Lead the team effectively and efficiently across the HR value chain including recruitment, performance management, retention of critical staff, succession planning, development skills, coaching and talent management.
• Optimise and manage performance and motivation by holding managers accountable for developing their staff and themselves.
• Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression opportunities for self with input from management.

Essential Qualifications - NQF Level

• Matric / Grade 12 / National Senior Certificate
• Professional Qualifications/Honour’s Degree

Preferred Qualification

• Masters Degree Computer Science, Econometrics , Mathematical Statistics , Actuary Science 

Preferred Certifications

• SAS Data Scientist certification , Microsoft Data Scientist , IBM data engineer

Minimum Experience Level

• MS/PhD in computer science, statistics, or operations research or related technical discipline
• 5-7 years’ experience in a statistical and/or data science role
• 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