Assistant Manager, Data Scientist

I&M Bank is a wholly owned subsidiary of I&M Holdings Limited, a publicly quoted company at the Nairobi Securities Exchange (NSE). The bank possesses a rich heritage in banking.

Assistant Manager, Data Scientist

Job Purpose

• The Data Scientist will develop and implement data science models and analytical solutions that address business challenges and uncover growth opportunities.

• The Data Scientist applies statistical techniques, machine learning algorithms, and data science methods to derive insights and support evidence-based decisions.

Roles & Responsibilities

Key Responsibilities

Strategic:

• Stay abreast of new ML/AI methods and propose applicable solutions.

• Align model development efforts with broader team priorities and ethics guidelines.

• Provide input into project scoping and business value estimation.

Initiatives:

• Design, develop, and deploy machine learning models.

• Clean, prepare, and engineer features from structured and unstructured data.

• Collaborate with stakeholders to ensure models address real business problems.

• Present insights and model results in understandable formats.

Operational:

• Write production-ready code and maintain model pipelines.

• Conduct peer reviews and contribute to code repositories.

• Document assumptions, methodologies, and model limitations.

• Monitor model performance and recalibrate as needed.

• Contribute to internal knowledge sharing and continuous learning efforts.

Key Responsibilities

Problem Scoping:

• Work with business teams to define problems.

• Frame use cases into model-ready formats.

• Perform initial feasibility assessments.

Data Preparation:

• Extract, clean, and prepare data.

• Conduct exploratory data analysis.

• Engineer relevant features.

Model Development:

• Build machine learning/statistical models.

• Train and tune models using appropriate metrics.

• Evaluate performance and robustness.

Insight Communication:

• Visualize and interpret results.

• Translate findings into business language.

• Support adoption and stakeholder understanding.

Deployment and Monitoring:

• Package models for deployment (API, batch, etc.)

• Monitor performance and drift.