One of our clients in the Banking sector are looking for a Data Scientist to join their team.
Job Purpose
Join an exciting, fun, data science team who are passionate about what they do and have fun while doing it. We
work hard and play hard, and we have an impact on our customers. We have many solutions in Production, we
are code first open-source enthusiasts, and we design, prototype, and build next-generation analytic engines
and services by applying strong expertise in machine learning, data mining and information retrieval.

Job Responsibilities
• Develop best-in-class statistical models and algorithms
• Acquire and load relevant data and generate features from this data sets.
• Implement and integrate models into production systems.
• Study and transform data science prototypes.
• Design machine learning systems.
• Research and implement appropriate ML algorithms and tools.
• Develop machine learning applications according to requirements.
• Select appropriate datasets and data representation methods.
• Run machine learning tests and experiments.
• Lead and develop Data Science Use Cases with a small team in an agile.
• 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 into 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.
• 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,
• Work with large data sets, simulation/ optimization and distributed computing tools
(Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.).
• 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
Organisationand 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.
• 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
Preferred Qualification
Masters Degree Computer Science, Econometrics , Mathematical Statistics , Actuary Science
Preferred Certifications
• SAS Data Scientist certification , Microsoft Data Scientist , IBM data engineer
• Any Data Science certificates from Coursera, EDSA, etc.
Minimum Experience Level
• S/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
Technical / Professional Knowledge
• Analysing situations or data that requires an in depth evaluation of multiple factors
• Data Mining
• Data Warehousing
• Financial modelling and analytics
• Research and analytics
• Strategy planning and execution
Behavioural Competencies
• Decision Making
• Innovation
• Technical/Professional Knowledge and Skills
• Customer Focus
• Applied Learning
• Continuous Improvement