Data Scientist

Job Description

To plan, build, optimise and implement innovative quantitative analytical methodologies, procedures, products and advanced
mathematical models that provide analytical support and interpret insights, using advanced analytics technologies, to address business opportunities and problems and implement business strategy.

• Lead a small team of high performing entry to senior level Data Scientists in Credit Collections Analytics environment.
• Use statistical methods and tools to analyze data and identify trends, pattens and draw insights.
• Build, implement and monitor a range of data driven statistical models to improve credit collections processes, customer experience and business profitability.
• Create delivery plans for achievement of outputs / deliverables in collaboration with business stakeholders to understand information requirements for strategy delivery and define metrics that track performance.
• Drive project planning, prioritizing and efficient project delivery.
• Build strategic solutions that analyze processes to recommend areas for optimization to achieve cost savings, revenue generation and efficiency improvements for the business.
• Adhere to model building policies, standards, frameworks, and governance process.
• Plan and perform regular model updates that capture evolving business complexity in current models.
• Drive process automation, optimization and productionalize existing and new business strategies and models into relevant platforms.
• Foster a culture of learning, upskilling and excellence withing your high performing team.
• Foster strong relationships with stakeholders, building trust and ensuring effective communication.
• Continuously challenge the status quo and contribute to the innovation and strategic direction of the department.
• Ensure own ethical usage of information that complies to restrictions applied for privacy and sensitivity classification.
• Collaborate with numerous departments across the business to improve processes and eliminate duplication of efforts.
• Build and sustain collaborative working relationships with relevant peers and stakeholders to achieve productivity synergies.
• Serve as SME for analytics applying own understanding of the operations of the business product or service.
• Implement Machine learning mathematical algorithms and automation techniques using open-source programming languages such as SAS or Python libraries.
• Utilise data to model complex abstractions in machine learning research to enable deep learning.
• Challenge current models to ensure relevance and accuracy of outputs.
• Take all necessary actions to ensure compliance with relevant statutory, legislative, policy and governance requirements in area of accountability.
• Ensure compliance is adopted in terms of systems and procedures as laid out by business.
• Document developed models, business processes, project specifications to address specific business requirements.

Ideal Candidate:

• Strong technical and statistical modelling skills.
• Knowledge of machine leaning methodologies data and analytics.
• Understanding of credit collections and operational processes.
• Understanding of the credit life cycle.
• Strong stakeholder management skills

Minimum Requirements:

• Bachelor’s degree in actuarial science, Quantitative Risk, Mathematics, or Statistics or similar.
• Honours or master’s degree would be advantageous.
• 5-8 years' experience in a similar role with leadership experience.
• Proficient in SAS and SQL

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Job Details

Take note that applications will not be accepted on the below date and onwards, kindly submit applications ahead of the closing date indicated below.

24/02/25

All appointments will be made in line with FirstRand Group’s Employment Equity plan. The Bank supports the recruitment and advancement of individuals with disabilities. In order for us to fulfill this purpose, candidates can disclose their disability information on a voluntary basis. The Bank will keep this information confidential unless we are required by law to disclose this information to other parties.