Available Jobs at Kuda

Role Overview

• We’re looking for a Head of Creative to lead Kuda’s rebrand and make it shine across everything we do. You’ll help position Kuda for the future while making sure we stay relatable, bold, and unmistakably Kuda. This is a hands-on leadership role - you’ll be shaping strategy, inspiring a talented creative team, and rolling up your sleeves to bring big ideas to life.

Key Responsibilities

• Lead the rebranding of Kuda alongside our agency partner and implement it consistently across all channels and touchpoints.
• Develop and oversee a cohesive creative strategy that aligns with business goals and resonates with target audiences.
• Manage, mentor, and inspire the creative team to deliver high-quality, innovative work.
• Collaborate cross-functionally with Product, Marketing, and Customer Experience teams to ensure brand consistency and impact.
• Define and maintain visual and verbal brand guidelines.
• Drive the development of creative campaigns, and experiences that enhance brand perception and engagement.
• Monitor creative performance and provide insights to optimize campaigns and brand initiatives.
• Stay ahead of trends in fintech, design, and brand experience to ensure Kuda remains a market leader.

Requirements

• 7–8 years of experience in creative leadership, preferably in fintech or tech-focused industries.
• Proven experience leading and managing creative teams.
• Strong portfolio demonstrating expertise in branding, visual identity, and integrated campaigns.
• Hands-on understanding of design and creative processes, with proficiency in key creative tools.
• Strategic thinker with excellent communication and stakeholder management skills.
• Experience in translating business goals into compelling creative solutions.
• Fintech experience is advantageous.

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Role Overview

• We’re looking for a Head of Creative to lead Kuda’s rebrand and make it shine across everything we do. You’ll help position Kuda for the future while making sure we stay relatable, bold, and unmistakably Kuda. This is a hands-on leadership role - you’ll be shaping strategy, inspiring a talented creative team, and rolling up your sleeves to bring big ideas to life.

Key Responsibilities

• Lead the rebranding of Kuda alongside our agency partner and implement it consistently across all channels and touchpoints.
• Develop and oversee a cohesive creative strategy that aligns with business goals and resonates with target audiences.
• Manage, mentor, and inspire the creative team to deliver high-quality, innovative work.
• Collaborate cross-functionally with Product, Marketing, and Customer Experience teams to ensure brand consistency and impact.
• Define and maintain visual and verbal brand guidelines.
• Drive the development of creative campaigns, and experiences that enhance brand perception and engagement.
• Monitor creative performance and provide insights to optimize campaigns and brand initiatives.
• Stay ahead of trends in fintech, design, and brand experience to ensure Kuda remains a market leader.

Requirements

• 7–8 years of experience in creative leadership, preferably in fintech or tech-focused industries.
• Proven experience leading and managing creative teams.
• Strong portfolio demonstrating expertise in branding, visual identity, and integrated campaigns.
• Hands-on understanding of design and creative processes, with proficiency in key creative tools.
• Strategic thinker with excellent communication and stakeholder management skills.
• Experience in translating business goals into compelling creative solutions.
• Fintech experience is advantageous.

go to method of application »

Role Overview

• As the Data Science Manager at Kuda, you will be responsible for leading a dynamic team of data scientists to develop and deploy machine learning models that drive critical business outcomes across the entire credit lifecycle. Your team will focus on building solutions for credit scoring, fraud detection, and collections, while also supporting various other business functions by providing data-driven insights and predictive capabilities.
• You will work with cutting-edge technologies in data science and machine learning, with an emphasis on building scalable, real-time decisioning systems that are integrated into our product offerings. This means that your models will not only be developed but also put into production in a way that supports live, real-time decisions, enhancing Kuda's ability to serve customers with speed and precision.
• Your role will require collaboration across multiple cross-functional teams, including product, business, technology, and data teams, ensuring that all teams are aligned to deliver value through innovative, data-driven solutions. As a manager, you'll foster an environment of continuous learning and improvement, ensuring that your team stays ahead of the curve in terms of industry trends, emerging technologies, and the most effective methodologies in the field of data science.
• Key to your success will be your ability to translate business challenges into data-driven solutions while balancing technical execution with strategic vision. Your leadership will help scale Kuda’s impact, bringing high-quality, machine learning-based credit solutions to millions of customers across Nigeria and beyond.
• This role will be a 50/50 split between leadership and hands - on - work - you will guide & mentor your team while also remaining deeply involved in the technical aspects.

Key Responsibilities

• Team Leadership: Manage and mentor a team of data scientists, fostering a collaborative and innovative environment.
• Model Development: Lead the design, development, and deployment of machine learning models for credit scoring, fraud detection, and collections.
• Cross-Functional Collaboration: Work closely with product, engineering, and compliance teams to integrate models into production systems.
• Data Analysis: Analyze large, complex datasets to extract actionable insights and inform business strategies.
• Model Monitoring: Oversee the performance of deployed models, ensuring they meet business objectives and regulatory standards.
• Stakeholder Communication: Present findings and recommendations to senior leadership and other stakeholders.
• Continuous Improvement: Stay abreast of industry trends and emerging technologies to continuously enhance model performance and team capabilities.

Requirements

• Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• Experience: Minimum of 6 years in data science, with at least 2 years in a leadership role managing teams and projects.
• Technical Skills: Proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). Strong knowledge of cloud environments and services (AWS, Google Cloud).
• Domain Knowledge: Experience in credit risk modeling, fraud detection, or financial services is highly desirable.
• Leadership: Strong ability to lead teams, manage projects, and communicate effectively with both technical and non-technical stakeholders.
• Regulatory Awareness: Understanding of financial regulations and compliance standards, particularly in the Nigerian context.

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Role Overview

• We are expanding and seeking a Data Engineer to join our ranks and champion growth. With a passion for data-driven decision-making, you will play a pivotal role in shaping the future of banking for millions.

Roles and responsibilities

• Design, build, and maintain scalable data ingestion and processing pipelines that support analytics, machine learning, and operational use cases.
• Integrate and transform data from diverse structured and unstructured sources into trusted, high-quality datasets.
• Collaborate with business stakeholders to translate analytical and operational needs into efficient data models and pipelines.
• Monitor and optimise data pipeline performance, ensuring reliability, observability, and cost efficiency.
• Support data quality, lineage, and metadata management through governance-aligned frameworks and automation.
• Enable prescriptive and predictive analytics by preparing and curating datasets for machine learning models.
• Partner with data scientists and ML engineers to deploy and operationalise ML models into production pipelines.
• Continuously evaluate and implement modern tools and frameworks to improve data acquisition, orchestration, and delivery.
• Develop analytical datasets, metrics layers, and transformations that power dashboards, self-service analytics, and advanced insights.
• Collaborate closely with data architects, platform engineers, and business teams to ensure alignment between data strategy, architecture, and delivery.

Requirements

• 3–5 years of hands-on experience as a Data Engineer or in a similar data-focused engineering role.
• Strong proficiency in SQL, including advanced query design, optimisation, and performance tuning.
• Proven experience working with relational databases such as Microsoft SQL Server, Azure SQL Database / Managed Instance, or PostgreSQL.
• Demonstrated ability to integrate, transform, and consolidate data from heterogeneous sources (e.g., Azure SQL, SQL Managed Instances, or BigQuery) into analytics-ready datasets on Google Cloud Platform (GCP) using BigQuery and visualised through Looker or similar BI tools.
• Exposure to ETL/ELT frameworks such as SQL Server Integration Services (SSIS), dbt Cloud, or Dataform.
• Skilled in the design, implementation, monitoring, and optimisation of modern data platforms and pipelines to support analytical and operational workloads.
• Experience with Azure Data Factory (ADF) or similar orchestration tools is a strong advantage.
• Familiarity with one or more programming languages such as Python, Java, Scala, R, or C# (Python preferred).
• Experience applying modern software engineering practices, including version control, CI/CD, and Agile methodologies.
• Strong computational and analytical thinking skills, with the ability to design efficient and scalable data solutions.
• Bachelor’s degree in computer science, Engineering, or related technical discipline or equivalent practical experience in data engineering.
• Data Stack: Azure Microsoft SQL Server (MI), Fivetran, Airbyte, Google Big Query, Google Cloud Platform (GCP), Dbt Cloud, DataForm (GCP), Looker.

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Role Overview

• We are looking for a Data Architect to oversee the design, governance, and optimisation of our organisation’s data architecture. This role will blend strategic vision with practical expertise in modern data engineering. The goal is to ensure that our data ecosystem supports advanced analytics, artificial intelligence, and real-time decision-making, all while adhering to industry best practices, such as the principles outlined in DAMA-DMBOK.

Roles and responsibilities

• Define and maintain the enterprise data architecture blueprint aligned with business strategy, DAMA-DMBOK principles, and modern data platform best practices.
• Collaborate with enterprise architects to ensure data architecture is fully integrated into the overall IT and business architecture.
• Lead the adoption of data modelling standards (conceptual, logical, and physical), including dimensional modelling and data vault methodologies.
• Oversee Master Data Management (MDM) strategy, implementation, and governance across domains such as Customer, Product, and financial data.
• Ensure architectural compliance with data governance policies, security frameworks, and regulatory requirements (GDPR, NDPR, ISO 27001).
• Design scalable, secure, and high-performance data solutions across multi-cloud and hybrid environments (Azure SQL, Google BigQuery, on-prem SQL Server).
• Define integration patterns for batch and streaming data ingestion using tools such as Airbyte, Azure Data Factory, and FiveTran.
• Oversee transformation layer design using Dataform and dbt. Cloud, ensuring version control, testing, and deployment best practices.
• Recommend and implement data storage strategies, including Medallion Architecture, Data Mesh, and Lakehouse patterns.
• Collaborate with infrastructure teams to provision infrastructure-as-code (Terraform or Pulumi) for data workloads.
• Partner with Data Governance teams to establish and enforce metadata management, data lineage, and business glossary standards.
• Define data quality frameworks and embed automated validation and anomaly detection in ingestion and transformation pipelines.
• Champion data stewardship practices across the business.
• Act as the primary authority on data architecture, advising C-level executives, engineering teams, and business stakeholders.
• Mentor senior data engineers, analysts, and modellers on best practices in architecture, modelling, and governance.
• Facilitate cross-functional workshops to align business requirements with architectural design.
• Stay ahead of industry trends, recommending emerging tools and patterns for modern data platforms.
• Continuously optimise cost, performance, and scalability of data platforms.
• Lead proof-of-concept initiatives for innovative data solutions, including AI- driven data management tools.

Requirements

• 10+ years in data-focused roles, with 3+ years in data architecture or enterprise architecture positions.
• A Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field is required.
• DAMA-DMBOK knowledge required; CDMP (Certified Data Management Professional) or equivalent certification preferred.
• TOGAF, Zachman, or Certified Enterprise Architect certification is an advantage.
• Advanced expertise in data modelling (conceptual, logical, physical) and MDM frameworks.
• Strong SQL skills with proven experience in Azure SQL, Google BigQuery, and Microsoft SQL Server.

Hands-on experience with:

• Ingestion: Airbyte, Azure Data Factory, Fivetran
• Transformation: Dataform, dbt Cloud
• Processing: Apache Beam/Dataflow, Spark
• Streaming: Kafka, Pub/Sub, Spark Streaming, or Flink
• Strong knowledge of modern data architectures (Medallion, Data Mesh, Lakehouse).
• Familiarity with orchestration tools (Airflow, Cloud Composer, Workflows).
• Proficiency in infrastructure-as-code (Terraform, Pulumi).
• Understanding of data security and compliance best practices.

Preferred Skills

• Experience in cloud cost optimisation for data workloads.
• Familiarity with data catalogue tools such as Collibra, Alation, or Data Catalogue.
• Experience in BI integration (Looker, Power BI, Data Studio).
• Exposure to machine learning data pipelines (Vertex AI, MLflow).

Data Stack

• Databases: Microsoft SQL Server, Azure SQL, Google BigQuery
• ngestion: Airbyte, Fivetran, Azure Data Factory
• Processing & Modelling: Dataform, dbt Cloud, Apache Beam/Dataflow, Spark
• Visualisation: Looker, Data Studio
• Cloud: Azure, Google Cloud Platform
• Orchestration: Airflow, Cloud Composer, Workflows
• IaC: Terraform, Pulumi