To design, prototype, and build next-generation analytic engines and services by applying strong expertise in maching learning , data mining and information retrieval
Develop best-in-class statistical models and algorithms
Conducts advanced statistical analysis
Provide actionable insights, identify trends, and measure performance
Create value out of enterprise wide data
Provide insights to BI and BA to further exploit and present their models
Provide strategic direction ito data information received
Apply advanced analytical techniques such as machine learning and artificial intelligence in order to derive business value.
Conduct data discovery for inclusion in models.
Collaborate with key stakeholders to obtain business acumen and intellectual property
Keep abreast with latest tools and techniques
Understands business problems and designs end-to-end analytics use cases
Collaborates with model developers to implement and deploy scalable solutions
Develop complex models and algorithms that drive innovation throughout the organization.
Ensure improvement of on-time performance and network planning,
Provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders.
Work with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.).
Ensure understaning of pros and cons of different analytics approaches for problem type.
Implements more advanced algorithms, e.g., complex descriptive.
Ensure Quality controls of own work and those of junior scientists.
Understand current state of analytics more broadly and apply techniques from across industries.
Map problems and quantify the impact of proposed measures.
Develop and prioritise use case roadmaps
Support the achievement of the business strategy, objectives and values by reviewing Nedbank and Business Unit Plan and ensuring delivered systems, process, services and solutions are aligned.
Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression for self through input and feedback from managers.
Ensure personal growth and enable effectiveness in performance of roles and responsibilities by ensuring all learning activities are completed, experience practiced and certifications obtained and/or maintained within specified time frames.
Enable skilling and required corrective action to take place by sharing knowledge and industry trends with team and stakeholders during formal and informal interaction.
Obtain buy-in for developing new and/or enhanced processes (e.g. operational processes) that will improve the functioning of stakeholders' businesses by highlighting benefits in support of the implementation of recommendations.
Support the achievement of the business strategy, objectives and values
Stay abreast of developments in field of expertise
Ensure personal growth and enable effectiveness in performance of roles and responsibilities
Contribute to the Nedbank Culture building initiatives (e.g. staff surveys etc.).
Participate and support corporate responsibility initiatives for the achievement of business strategy
Seek opportunities to improve business processes, models and systems though agile thinking.
Essential Qualifications - NQF Level
Matric / Grade 12 / National Senior Certificate
Advanced Diplomas/National 1st Degrees
BSC Computer Science, BSc Engineering, Econometrics, Mathematical Statistics , Actuary Science or any Stem Qualification.
Machine Learning and Data engineer related
Type of Exposure
Minimum Experience Level
5-7 years' experience in a statistical and/or data science role
Technical / Professional Knowledge
Deep knowledge of machine learning, statistics, optimization or related field
Experience in Python(Must), R and one additional language (SAS, Java Lua, Clojure, Scala, etc)
Experience working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.)
Experience in end to end Use case delivery
Ability to translate data narrative to business narrative
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
ML Ops (Cloud Devops) is an added advantage.
ML Ops (ML engineering – running a Data Science platform) is an added advantage.