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Job Description
JOB PURPOSE
To apply advanced analytics and data science techniques/approaches and produce MIS reports/dashboards in order to support modeling activities, reporting and campaign execution
ACCOUNTABILITIES
Data Science: Determine and apply the right supervised/non-supervised machine learning technique(s) using all types of data sources (For example; online/offline, structured/unstructured) in order to solve various analytical problems and use cases Measure, document and communicate the pact/return on investment (ROI) of delivered use cases/analytical models and propose necessary updates/refinements in order to maintain the accuracy of developed models Attend forums/seminars/courses and conduct research/reading in order to stay up to date on the latest analytical/big data/machine learning developments and make recommendations/suggestions on the most effective modeling approaches
Reports and Dashboards: Develop consistent/standardised report formats and continually refine ‘on demand’ MIS/dashboards for key stakeholders in order to ensure/maintain accuracy of information/data provided
Policies, Processes, Systems and Procedures: Adhere to all relevant organisational and departmental policies, processes, standard operating procedures and instructions so that work is carried out to the required standard and in a consistent manner while delivering the required standard of service to customers and stakeholders
Self-Management: Manage self in line with the bank’s people management policies, procedures, processes and practices to ensure adherence and to maximise own contribution to business performance
Customer Service: Demonstrate Our Promise and apply the ADCB Service Standards to deliver the bank’s required levels of service in all internal and external customer interactions
Skills
EXPERIENCE, QUALIFICATIONS & COMPETENCIES
Minimum Experience
At least 2 - 4 years of experience in data science with knowledge of advanced analytics techniques and big data tools and hands on experience of business/data analysis
Minimum Qualifications
Bachelor’s Degree in Statistics, Physics, Mathematics, Computer Science, Engineering or related field
Knowledge and Skills
Knowledge of machine learning and data mining techniques (Regression, decision tree, neural network, random forest, SVM
etc.) and statistics concepts
Experience in handling large amounts of all types of data from different sources
Proficiency with SAS and SQL
Experience with visualization tools (Tableau, QliK Sense, SAS VA etc.)
Microsoft Office (Word; excel and PowerPoint)
Knowledge of programming languages (Python, Java, Scala, R)
Experience with the Hadoop ecosystem (MapReduce, Hive, Pig, Spark, HBase etc.)
Ability to work in a multidisciplinary environment (IT, Business, Marketing etc.)
Analytical and data interpretation skills
Planning and time management skills
Written and verbal English