Qualifications Education: Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field Master’s Degree in a Data Science, AI/ML, Statistical or related field (preferred) MBA or Masters (advantageous) Experience: (8+ yrs of Relevant exp) 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 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 #J-18808-Ljbffr