Data Science Manager at Kuda Technologies Ltd

, , United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

29 Jan, 26

Salary

0.0

Posted On

31 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Credit Scoring, Fraud Detection, Data Analysis, Python, SQL, Cloud Environments, AWS, Google Cloud, Team Leadership, Project Management, Stakeholder Communication, Regulatory Awareness, Continuous Improvement, Model Monitoring

Industry

Financial Services

Description

Kuda is a money app for Africans on a mission to make financial services accessible, affordable and rewarding for every African on the planet. We’re a tribe of passionate and diverse people who dreamed of building an inclusive money app that Africans would love so it’s only right that we ended up with the name ‘Kuda’ which means ‘love’ in Shona, a language spoken in the southern part of Africa. We’re giving Africans around the world a better alternative to traditional finance by delivering money transfers, smart budgeting and instant access to credit through digital devices. We’ve raised over $90 million from some of the world's most respected institutional investors, and we’re rolling out our game-changing services globally from our offices in Nigeria, South Africa, and the UK. 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. 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. Why join Kuda? At Kuda, our people are the heart of our business, so we prioritize your welfare. We offer a wide range of competitive benefits in areas including but not limited to: 💜A great and upbeat work environment populated by a multinational team 👴Pension 📈Career Development & growth 😁Competitive annual leave plus bank holidays 🎁Competitive paid time off (Parental, Moving day, Birthday, Study leave etc) 💯Group life insurance 💖Medical insurance 🎁Well-fare package (Wedding, Compassionate and etc) ✅ Perkbox 🏃‍♀️Goalr - employee wellness app 🥇Award winning L&D training 💒 We are advocates of work-life balance, working in a hybrid in office schedule Kuda is proud to be an equal-opportunity employer. We value diversity and anyone seeking employment at Kuda is considered based on merit, qualifications, competence and talent. We don’t regard colour, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status. If you have a disability or special need that requires accommodation, please let us know.

Responsibilities

Lead a team of data scientists to develop and deploy machine learning models for credit scoring, fraud detection, and collections. Collaborate with cross-functional teams to integrate models into production systems and ensure they meet business objectives.