Predictive Analyst

About the role

We are seeking an experienced Data / Decision Scientist to join our team. As a Predictive Analyst , you will be working with and enhancing our prediction pipelines code base, to enable prediction at scale across our many jurisdictions and within EZRA's array of credit products (term and revolving), and to drive new and existing business performance - specifically focused on balancing revenue and bad debt, i.e. net revenue optimisation. You will be responsible for designing and developing tools to enable fast model development, conducting experiments, and developing data-driven solutions to solve complex problems. The ideal candidate should have strong analytical and problem-solving skills, in addition to high proficiency in Python and SQL , with experience in developing machine learning systems utilizing software engineering principles. Previous experience in fintech , specifically credit decisioning systems, airtime credit services or mobile money lending leveraging alternate data is further advantageous.

Responsibilities

• Data Strategy & Preparation: Review and identify key datasets from partners to develop robust ML models. Collect, preprocess, and analyze large, complex datasets to ensure data integrity.
• Feature Engineering: Define features and perform advanced clustering, feature reduction, and selection techniques.
• Model Development: Build predictive models to improve partner and product performance, developing specific "Ezra Prediction" modules in Python for automated ML systems.
• Experimental Design: Design and conduct experiments (A/B testing) to validate models and hypotheses, enhancing overall market understanding.
• Deployment & Collaboration: Partner with cross-functional teams to implement and deploy machine learning solutions into production environments.
• Insight Communication: Translate complex findings into actionable insights for both technical and non-technical stakeholders through reports and visualizations.
• Optimization: Continuously monitor and iterate on model performance, prediction systems, and underlying algorithms.
• Essential Qualifications and Experience:
• Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Professional Experience: 5+ years of experience in a Data / Decision Science or Machine Learning Engineering role with a proven track record.
• Technical Proficiency:
• Expert-level Python programming skills.
• Advanced SQL skills (Postgres, Redshift, or similar).
• Deep understanding of data structures (lists, dictionaries, arrays, data frames).
• Data visualization / analysis / statistical inference.
• Core Competencies: Strong analytical and problem-solving skills, with the ability to work effectively both independently and within a team.
• Communication: Exceptional story-telling and presentation skills, specifically the ability to bridge the gap between technical complexity and business logic.
• Beneficial Qualifications and Experience:
• MLOps & Production: Experience operationalizing ML models into production with measurable impact on product and financial optimization.
• DevOps Tools: Proficiency with Source Control Management (Git/Bitbucket) and CI/CD pipelines (e.g., Jenkins).
• Architecture: Understanding of Feature Store architecture and implementation.
• Environment: Experience working in Linux OS variants (Debian) and comfort utilizing the command line.
• Agility: Ability to balance "start-up" stage project work with the development of long-term scalable ML modules.
• Language Skills: Proficiency in French is beneficial to support operations across various jurisdictions.
• The Ideal Candidate:
• Innovation-Driven: Passionate about deploying customer-centric products that exceed quality and delivery expectations.
• Growth Mindset: Proud of their work but driven by continuous improvement; able to self-critique and accept constructive feedback.
• Detail-Oriented: High attention to detail with a commitment to process, procedure, and documentation as pillars of excellence.
• Adaptable: Comfortable stepping outside of their comfort zone to learn new tasks and technologies.
• Company overview:
• Our flagship products are Airtime Credit Services (ACS), Nano and BNPL.
• ACS is an airtime or data advance offered to prepaid mobile subscribers at the point of low credit.
• Nano is a micro cash advance offered to mobile wallet users on demand.
• BNPL facilitates payment installments for products and services
• As a FinTech company, our business is entirely technology and data driven, from

Additional Information

Predictive Analyst Location: Dubai, United Arab Emirates or Nairobi, Kenya Reports to: Director of Prediction & Data

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