Data Scientist

Role : Data Scientist
Location : Johanesburg, South Africa

IMPORTANT:
Pls mention for each profile segregated experience for..
5+ years of relevant work experience as a Data Scientist
2+ years owning production AI/ML.
3+ years in non-traditional FinTech, Banking or Financial Services Sector


Responsibilities:
The Data Scientist is responsible for driving the analytical, statistical, and programming interpretation of data to support decision making and drive business results.
The Data Scientist supports product, teams with insights gained from analysing company & customer data to provide business predictions, proposals, and recommendations to improve business outcomes.
Drive measurable business outcomes by turning data into automated decisions by building active tools triggering an automated action.
To lead and provide expertise on Big data and AI initiatives, analysing business requirements and designing appropriate models and ensuring application architecture alignment.
Translate business strategy into AI use cases that drive measurable value (e.g., revenue growth, efficiency gains, risk reduction).
Utilize advanced algorithms and analytics to manage large transactional wallet datasets, optimizing profitability through precise risk assessment & strategic decision-making
Develop and deploy advanced models and algorithms, ensuring robust and accurate risk assessment to support effective management strategies
Integrate AI seamlessly with existing data, BI, and operational platforms.


Education:
Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field
Masters Degree in a Data Science, AI/ML, Statistical or related field (preferred)
MBA or Masters (advantageous)


Experience:
5 or more years of relevant work experience as a Data Engineer/ Data Scientist
46+ years applied data science; 2+ years owning production AI/ML.
At least 3 years experience within a non-traditional FinTech, Banking or Financial Services Sector
Experience in Data Science and Data Analysis with a specific focus on AI/ ML models within banking, finance and/or telecommunications industry
Proven delivery of automated decisioning (recommendation/propensity/fraud/forecasting) with quantified business impact.
Experience in Data Engineering within banking or financial services industry
Understanding of enterprise-scale systems and technologies used in data infrastructures
Experience of working in an Agile/DevOps environment
GitHub or GitLab experience for CI/CD
Proficient in working with open-source languages such as Python, Jupyter Notebook, R / Spark - Scala and others to drive optimized data engineering and machine learning best practise frameworks
Working knowledge in Hadoop, Apache Spark and related Big Data technologies and their applications in data engineering and MLOps pipelines
AI/ Machine learning for predictive modelling and other relevant use cases
Understanding of FinTech, banking, microfinance and payment businesses