Business, strategic management Jobs for Mid-level in Africa

95 jobs found

M-KOPA

Business Analyst - Credit Eligibility

Nairobi

Kenya

M-KOPA

Senior People Partner

Nairobi

Kenya

Takataka Solutions

Team Leader — Sorting Operations

Nairobi

Kenya

Movit Products Limited

Risk Manager

Kampala

Uganda

M-KOPA

Senior People Partner - Commercial

Nairobi

Kenya

Stanbic IBTC Bank

Manager, Relationship, Commercial Banking

Maiduguri

Nigeria

Kuda Bank

Product Manager Lead

Lagos

Nigeria

Matrix Energy Group

Retail Station Supervisor

Akure,

Effurun,

Ekpoma

Nigeria

+ 1 more
MTN Nigeria

Specialist - International Remittance (Product Manager)

Lagos

Nigeria

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Management Sciences for Health

M&E Specialist

Abeokuta

Nigeria

Country / Region

Profession (Mid-level)

Seniority (Business, strategic management)

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M-KOPA

Finance & FinTech

Business Analyst - Credit Eligibility

Job details

Contract Type

Description

Your application should demonstrate:

  • Several years in roles with significant analytical components

  • Strong statistical modeling and quantitative analysis skills, including the ability to conduct your own analysis of unstructured data

  • Fluency in Python, SQL, and other relevant tools for data analysis

  • Experience translating complex data insights into actionable business strategies

  • Ability to work cross-functionally with product, engineering, and commercial teams

  • Strong data communication skills — written, oral, and visual

  • Strong interpersonal and collaboration skills

  • (Nice to have) Experience in credit, underwriting, or lending analytics


Responsibilities
  • Analyzing M-KOPA's repayments data and other data sources to continuously improve our loan eligibility criteria while managing credit risk

  • Refining loan pricing based on credit analysis and customer behavior

  • Testing new types of loans to understand customer demand and credit performance

  • Monitoring credit performance to detect risk shifts and quantify margin impact

  • Testing the predictiveness of new data sets for the purposes of eligibility criteria

  • Using Python, SQL, and other tools for data analysis to drive insights

  • Working with data scientists to leverage machine learning models as part of loan eligibility decisions


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