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.<\/p>\n
Minimum Requirements<\/p>\n
Experience<\/p>\n
\t5 or more years of relevant work experience as a Data Engineer\/ Data Scientist
\n\t4\u20136+ years applied data science; 2+ years owning production AI\/ML.
\n\tAt 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
\n\tExperience in Data Science and Data Analysis with a specific focus on AI\/ ML models within banking, finance and\/or telecommunications industry
\n\tProven 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
\n\tExperience of working in an Agile\/DevOps environment
\n\tGitHub or GitLab experience for CI\/CD
\n\tConsistent improvement CI\/CD applications for collaborations and enhancement to
\n\tdrive develop once and deploy to many mindset through container repositories
\n\tProficiency in working with Python and its relevant libraries SAS or R \/ Scala for data
\n\tclean up and advanced data analytics – Working knowledge in Hadoop, Apache Spark and related Big Data technologies
\n\t(MapReduce, PIG, HIVE) – Demonstrated experience utilizing software tools to query and report data and being
\n\tsoftware agnostic – Highly proficient in database management systems like Postgres, Oracle, Mongo,
\n\tMSSQL – Experience in data analysis and management, business performance management
\n\tand\/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
\n\tProficiency in working with data engineering capabilities that leverages both cloud
\n\t(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,
\n\tR \/ Spark – Scala and others to drive optimized data engineering and machine
\n\tlearning best practise frameworks – Strong analytical skills with ability to automate reports that tells a story through
\n\tvisualization by leveraging standard enterprise BI tools like Power BI, Data Studio,
\n\tElastic Search-Kibana and many others – Working knowledge in Hadoop, Apache Spark and related Big Data technologies and
\n\ttheir applications in data engineering and MLOps pipelines – Highly proficient in data warehouse and management for RDBMS and latest Big Data
\n\tcapability – Ability to design, deploy and maintain machine learning and predictive model for different business use cases
\n\tData 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<\/p>\n
Qualifications<\/p>\n
\tMinimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field
\n\tMasters Degree in a Data Science, AI\/ML, Statistical or related field (preferred)
\n\t\u00a0<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
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