Join our Team

At PaySwitch, we are dedicated to revolutionizing the way payments are processed, making transactions
secure, efficient, and hassle-free for businesses and consumers alike.

Current Openings

Find a role that fits your expertise

Payment Switching & Terminals Engineer

Mid Level 3 Accra, Ghana Full-Time

Provide application support, system administration, and technical expertise for payment switching platforms and terminals.

Data Engineer – Data Platforms & Analytics Enablement

3–6 Years Accra, Ghana Full-Time

Design, build, and maintain scalable data infrastructure and pipelines supporting analytics, modelling, and operational intelligence.

Data Scientist – Risk, Analytics & Platform Insights

3–6 Years Accra, Ghana Full-Time

Develop and validate data-driven models and analytical frameworks for credit platforms, risk decisions, and product insights.

Purpose & Scope

To provide application support, system administration, and technical expertise for payment switching platforms and terminals while ensuring operational excellence and risk management.

Position in Organisation

Reports To: Head, Payment Switching & Terminals
Responsible For: Payment Switching & Terminals
Budget Responsibility: N/A

Duties & Key Responsibilities

Provide application support including system administration, troubleshooting, root cause analysis, and incident resolution.
Serve as liaison between business, operations, and technical teams.
Lead testing and implementation of new processes, applications, and enhancements.
Coordinate User Acceptance Testing (UAT) and ensure release quality.
Review existing solutions and recommend improvements to reduce operational risk.
Lead development of unit and integration testing plans.
Ensure terminal preparation, deployment, and customer system setup.
Ensure compliance within company risk appetite and PCI-DSS regulations.
Identify product enhancements and assess system impact.
Perform other duties assigned by management.

Education & Experience

BA/BSc in IT or related discipline (MIS, Finance, Business).
Minimum 4 years' experience in Payments Products or Operations (Treasury, Card Services, Global Payments).

Specific Knowledge Requirements

Experience supporting EFT platforms and payment channels.
Proficiency in system administration.
Experience with commercial card processing systems.
Strong RDBMS knowledge (Oracle or MS SQL).
Experience in fraud/application support environments.
Unix shell scripting, .NET, C#, ASP.NET, PowerShell knowledge.
Understanding of PCI-DSS regulations.
Knowledge of payment processing and fraud prevention.
DevOps environment experience preferred.
Strong MS Office skills (Excel, Access, Outlook, Word).
Experience handling sensitive/confidential information.

Purpose & Scope

The role is responsible for designing, building, and maintaining scalable, reliable data infrastructure and pipelines that support analytics, modelling, reporting, and operational intelligence across PaySwitch. The role supports multiple use cases including credit platforms, internal analytics, product insights, and business intelligence.

Position in Organisation

Reports To: Head of Product, Innovation & Excellence

Duties & Responsibilities

Data Pipelines & Ingestion

Design and build robust data pipelines to ingest data from transaction processing systems, lending/BNPL/internal platforms, and external partners.
Support batch and near-real-time ingestion patterns.
Monitor pipeline performance and reliability.

Data Platforms & Storage

Manage and optimize data storage solutions across data lakes and warehouses.
Implement data models and schemas that support analytics and modelling.
Ensure historical data consistency and replicability.

Data Quality, Governance & Reliability

Implement data validation, reconciliation, and quality checks.
Maintain metadata, documentation, and lineage for critical datasets.
Support auditability and traceability of data used in analytics and models.

Collaboration & Enablement

Work closely with Data Scientists to enable feature generation and reproducible datasets.
Support BI tools and analytics workloads.
Collaborate with engineering teams to integrate data platforms into production systems.

Skills & Abilities

Technical

Strong proficiency in SQL for data modelling, transformation, and analysis.
Solid experience using Python for data processing and pipeline development.
Working experience with Apache Airflow or equivalent workflow orchestration tools.
Hands-on experience with Azure-native data services: Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics.
Experience with Apache Spark / PySpark or Azure Databricks.
Familiarity with ELT / ETL architectures, batch and event-based processing.
Working knowledge of Git and collaborative development workflows.
Exposure to C# in Azure or .NET environments is an advantage.
Familiarity with data quality, validation, and monitoring tools is an advantage.

Non-Technical

Strong attention to detail and reliability.
Structured and methodical problem-solving approach.
Clear documentation practices.
Ability to collaborate across technical and non-technical teams.
Strong ownership mindset.

Education & Experience

Degree in Computer Science, Engineering, Information Systems, or related field is advantageous but not mandatory.
3–6 years of demonstrable experience working as a Data Engineer or in data platform roles.
Proven experience building and maintaining production data pipelines.
Experience working in cloud-based data environments, particularly Microsoft Azure, is an advantage.
Exposure to fintech, payments, or transactional systems is a strong advantage.

Specific Knowledge Requirements

Data pipeline architecture and orchestration.
Data quality and governance practices.
Supporting analytics and modelling workloads.
Working with transactional and event-based data.
Cloud-based data platform operations.

Purpose & Scope

The role is responsible for developing, validating, and maintaining data-driven models and analytical frameworks that support PaySwitch's credit platforms, internal decision-making, product analytics, and operational intelligence. This is a hands-on individual contributor role requiring strong analytical thinking, practical modelling skills, and close collaboration with data engineering, product, and business teams.

Position in Organisation

Reports To: Head of Product, Innovation & Excellence

Duties & Responsibilities

Modelling & Advanced Analytics

Design and develop analytical and predictive models for credit scoring, risk assessment, internal performance analytics, and customer/transaction behavior analysis.
Build and evaluate regression and classification models including logistic and linear regression, decision trees, random forests, and gradient boosting models where appropriate.
Select modelling techniques based on interpretability, robustness, and business impact.

Feature Engineering & Data Exploration

Perform exploratory data analysis (EDA) across internal and external datasets.
Design features from transactional, behavioral, operational, and demographic data.
Collaborate with the Data Engineer to ensure features are reproducible and production ready.

Validation, Explainability & Governance

Conduct model validation, performance testing, and stability analysis.
Monitor model and analytical outputs for drift, bias, and degradation.
Produce clear documentation covering assumptions, feature rationale, metrics, and limitations.
Support internal reviews, audits, and decision forums.

Product & Platform Collaboration

Work closely with product teams to translate analytical insights into product requirements and UX decisions.
Contribute to Product and Functional Requirement Documents by defining analytical logic, thresholds, KPIs, and measurement frameworks.
Support experimentation, A/B testing, and hypothesis-driven product improvements.
Support deployment of models and analytics into production environments with engineering teams.
Continuously improve analytical methods, tools, and practices.

Skills & Abilities

Technical

Strong proficiency in Python for data analysis and modelling.
Working experience with SQL (advanced querying).
Experience with modern machine learning libraries and frameworks.
Familiarity with Azure data and analytics services: Azure Data Lake, Azure Synapse Analytics, Azure Machine Learning (working level), Microsoft Fabric (working knowledge).
Comfortable working with version control (Git) and collaborative workflows.

Non-Technical

Strong analytical and critical thinking skills.
Ability to explain complex concepts clearly to non-technical stakeholders.
Structured documentation and communication habits.
High ownership, curiosity, and accountability.
Ability to work across multiple problem domains simultaneously.

Education & Experience

Degree in Data Science, Statistics, Mathematics, Economics, Engineering, or related field is advantageous but not mandatory.
3–6 years of demonstrable experience working as a Data Scientist, Risk Analyst, or Platform Analytics professional.
Proven experience delivering models or analytics used in real business or production environments.
Experience in fintech, lending, payments, or transactional data environments is a strong advantage.

Specific Knowledge Requirements

Statistical modelling and classification techniques.
Feature engineering and data preparation.
Model evaluation and explainability concepts.
Working with large, real-world datasets.
Applying analytics to product, risk, and operational decisions.