Data Scientist

Description (Public)

The Data Scientist analyses complex datasets, develops and validates statistical, machine learning and generative AI models, and deploys model-driven solutions into production to support decision-making at Co-operative Bank of Kenya.

Duties, Roles and Responsibilities

Collaborate with business and product teams to identify priority business challenges, define analytical approaches and establish measurable outcomes
Analyse complex datasets to uncover trends, patterns and opportunities, translating findings into actionable insights and recommendations
Develop, train, test and validate statistical, machine learning, generative AI and optimisation models using robust and reproducible methodologies
Establish model performance benchmarks, validation criteria and monitoring frameworks, ensuring fairness, explainability, human oversight and compliance
Work with Data Engineers and Application Engineers to deploy models and AI solutions into production using approved MLOps/LLMOps practices
Design and conduct experiments, pilots and post-deployment evaluations to measure business impact
Monitor model effectiveness and business outcomes, identify performance deterioration or data drift and recommend recalibration, retraining or retirement
Maintain model documentation, code and validation evidence to support governance, audit and model management

Qualifications, Education and Competencies

Qualifications & Experience:

Bachelor's degree in Data Science, Statistics, Mathematics, Actuarial Science, Computer Science, Economics, Engineering, Operations Research or a related quantitative field
At least four (4) years of relevant experience in data science, advanced analytics, machine learning or applied AI
Demonstrated experience taking analytical or machine learning solutions from problem definition through validation to production deployment
A relevant master's degree or professional certification in data science, machine learning, cloud computing or AI is an added advantage

Skills & Competencies:

Proficiency in Python or R and SQL
Strong knowledge of statistical modelling, machine learning, feature engineering and model evaluation
Experience in credit, fraud, collections, customer analytics or banking operations is an added advantage
Strong communication and stakeholder engagement skills