Senior Data Scientist
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.
Minimum Requirements
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
- Consistent improvement CI/CD applications for collaborations and enhancement to
- drive develop once and deploy to many mindset through container repositories
- 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
- (MapReduce, PIG, HIVE) - 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 and others to drive optimized data engineering and machine
- learning best practise frameworks - Strong analytical skills with ability to automate reports that tells 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
- Masters Degree in a Data Science, AI/ML, Statistical or related field (preferred)
MBA or Masters (advantageous)
