9 MONTHS CONTRACT – Johannesburg-Hybrid We are looking for an experienced Senior Data Scientist with strong AI/ML expertise to join our dynamic team in the Banking/FinTech space. This role is ideal for someone who thrives in data-driven environments, enjoys solving complex problems, and has experience delivering production-ready AI/ML solutions. Experience 5 or more years of relevant work experience as a Data Engineer / Data Scientist 4–6+ 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; consistent improvement CI/CD applications for collaborations and enhancement to drive develop once and deploy to many mindset through container repositories. 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. Proficiency in working with Python and its relevant libraries, SAS or R / Scala for data. Clean up and advanced data analytics – working knowledge in Hadoop, Apache Spark and related Big Data technologies. Demonstrated experience utilizing software tools to query and report data and being software agnostic – highly proficient in database management systems like Postgres, Oracle, Mongo, MSSQL. Experience in data analysis and management, business performance management and/or reporting within the financial sector or banking industry; experience working in a medium to large organization; experience in ecommerce and electronic payment business is advantageous; experience working across global locations/regions and have a grasp of political, social, infrastructure and integrity challenges. Proficiency in working with data engineering capabilities that leverages both cloud (Azure, GCP or AWS) and on-premise infrastructure; CI/CD orchestrations and repository; proficient in working with open-source languages such as Python, Jupyter Notebook, R / Spark – Scala to drive optimized data engineering and machine learning best‑practice frameworks; strong analytical skills with ability to automate reports that tell a story through visualization by leveraging standard enterprise BI tools like Power BI, Data Studio, Elastic Search-Kibana, and many others; working knowledge in Hadoop, Apache Spark and related Big Data technologies and their applications in data engineering and MLOps pipelines; highly proficient in data warehouse and management for RDBMS and latest Big Data capability; ability to design, deploy and maintain machine learning and predictive model for different business use cases; data engineering, mining and analytics – AI/ Machine learning for predictive modelling and other relevant use cases – payment, E-Commerce and digital platforms – understanding of FinTech, banking, microfinance and payment business. Qualifications Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field. Master’s Degree in Data Science, AI/ML, Statistics or related field (preferred). MBA or Masters (advantageous) #J-18808-Ljbffr