Global Data Scientist Duties:

  • Define data modelling requirements, gather, and validate information, apply judgment and statistical tests, and develop data structures to support the generation of business insights and strategy;
  • Drive development of in-house credit models, particularly developing scorecard models, enhance credit risk models (Behavioral and Application Credit Scoring Models);
  • Utilize internal and external data sources and work on big data environment;
  • Work on data collection, data cleansing, methodology evaluation, model assessment, model refreshment, implementation testing and documentation;
  • Support implementation team(s) on model testing process including implementation specifications development, model testing development and execution to ensure model is appropriately implemented and produces output as designed;
  • Support throughout model lifecycle from model initiation to model retirement, including enhancements/recalibrations;
  • Execute monthly credit scoring models (internal) in accurate and timely manner for credit risk team;
  • Collect credit risk-related data and conduct analysis, segmentation, trending and forecasting;
  • Actively examine alternative, internal, and external data sources to propose and/or review credit expansion and/or tightening measures, presenting and discussing alternatives, advantages, and disadvantages based on the data and industry expertise;
  • Testing, validating, and overseeing the deployment of scorecards developed by external consultants for FIF;
  • Support ongoing BAU maintenance and upstream data changes into the enterprise data platforms;
  • Support data projects through the provision of requirement specifications, UAT and Post implementation validation;
  • Provide test interfaces for users to test the reports and dashboards before being put on the production environment and carry out technical user training as required to enable users to interpret BI solutions;
  • Adhere to set Data Management standards and support the implementation of FIF’s Data Strategy;
  • Channel data issues to relevant support teams and proactively track them to their conclusion;
  • Escalate any breach of SLAs or significant events to the Director Global Data Management;
  • Develop and maintain documentation/manuals on processes, procedures, models developed, reports generated, and statistical solutions devised;
  • Conduct other ad hoc analysis as needed.

Qualification Requirements:

  • Bachelor’s Degree preferably in Statistics, Mathematics, Actuarial Science, Computer science or a related quantitative field and at least 4 years of hands-on experience in a busy commercial banking environment. A master’s degree is an added advantage;
  • A minimum of 4 years of proven data science & analytics performance;
  • Experience with relational Databases such as Oracle, SQL queries, or OLAP cubes is preferred;
  • Experience in the development of Credit Score Cards is a requirement;
  • Experience with common Data Science toolkits, such as R, Python, Weka, NumPy, MatLab, etc;
  • Excellence in at least R and/or Python is highly desirable;
  • Experience in risk analytics (model development, strategy and framework, scorecard development, documentation, validation, governance, implementation, and automation etc.);
  • Experience with Machine Learning modelling techniques;
  • Understanding credit bureaus and non-traditional data providers;
  • Proficiency in using query languages such as SQL, Hive, and Pig and Experience with NoSQL databases, such as MongoDB, Cassandra, and HBase;
  • Good Applied Statistics skills such as Distributions, Statistical Testing, and Regression Analysis with good Scripting and Programming skills;
  • Knowledge of Agile Software Development process and performance metric tools;
  • Excellent understanding of Machine learning techniques and Algorithms, such as k-NN, Naive Bayes, SVM and Decision Forests;
  • Excellent understanding of data concepts and experience in data management capabilities including data definitions, data quality management and data integration;
  • Good presentation skills, business and technical writing, and verbal communication skills to support decision-making and actions;
  • Excellent problem-solving and critical thinking skills to recognize and comprehend complex data flow and designs;
  • Self-motivated and able to dynamically determine priorities;
  • Understanding of data governance issues, policies, regulatory requirements, and industry information affecting the business environment;
  • Proven ability to collaborate with other team members across boundaries and contribute productively to the team’s work and output, demonstrating respect for different points of view;
  • Able to use strong interpersonal and teamwork skills to cultivate effectively, productive user relationships and partnerships across the network;
  • Highest personal and professional integrity and strong work ethic;
  • Ability to articulate a vision of transformation efforts and a sense of mission;
  • Results orientation, willingness to commit to a direction and drive operations to completion;
  • Ability to break down complex problems and projects into manageable goals;
  • Ability to get to the heart of the problem and make sound and timely decisions to resolve problems;
  • Demonstrated ability to manage complexity and multiple initiatives coupled with the ability to synthesize and analyze diverse data and information, develop, and recommend strategies;
  • Ability to think creatively with a strategic perspective, highly driven and self-motivated;
  • Analytical with good project management and team leadership skills.