· Develop advanced ML (such as fraud etc) Credit scoring models for different business
· Scorecards using ensemble algorithms in python.
· Conduct EDA, data extraction, data cleaning and documentation of created models
· Engage central team ensuring laid down best practices are followed
· Develop models which do not deviate too much from developed algorithms for Kenya
· Engage business stakeholders to glean from domain knowledge in creating fit for purpose
· Ensure codes are refactored for data engineering pipeline
· Engage assigned data engineers to promote developed models to production
· Engage scrum masters and project managers in a timely manner on a periodic basis to provide project updates
· Delivering projects within the allocated timeline
· Multitask by building more than one algorithm at each time
· Proven development experience in software and software engineering.
· Understanding of financial services data processes, systems, and products.
· Experience in technical business intelligence.
· Knowledge of IT infrastructure and data principles.
· Project management experience.
· Exposure to governance and regulatory matters as it relates to data.
· Experience in building models (credit scoring, propensity models, churn, etc.).
· Candidate should have 5+ – 8 years of experience:
· Working with unstructured data (e.g. Streams, images)
· Understanding of data flows, data architecture, ETL and processing of structured and unstructured data.
· Using data mining to discover new patterns from large datasets.
· Implement standard and proprietary algorithms for handling and processing data.
· Experience with common data science toolkits, such as SAS, R, SPSS, etc.
· Experience with data visualisation tools, such as Power BI, Tableau, etc.
· Proficiency in application and web development. Structured and Unstructured Query
· languages e.g. SQL, Qlikview; SSIS SSRS, Python, JSON , C#, Java, C++, HTML