• Permanent
  • remote
  • Posted 4 months ago
  • Salary: Rs.as per industry
  • Exp: 5 to 10 years
  • Position: senior
  • Qualification: Any IT
  • Industry: IT



·         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

·        algorithms

·         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


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