Data Scientist - Financial Fraud Detection at Kuda Bank

Kuda is a full service, app-based digital bank. Our mission is to be the go-to bank not just for those living on the African continent, but also for the African diaspora wherever they might live, anywhere in the world. Kuda is free of ridiculous banking charges and great at helping customers budget, spend smartly and save more. We raised the largest seed round ever seen in Africa, and completed a Series A funding round in February 2021, led by some of the world's smartest venture capital investors. With offices in London (our HQ), Lagos and Cape Town, and further offices opening across Africa during 2021, Kuda is fast becoming recognised as the leading 'Neobank' for Africans.

To help us grow into the company that can bring meaningful change to the way people across Africa get access to great financial products and services in order to take control of their personal finances, we are actively looking for bright, talented, driven people who are excited by our mission. If this sounds like a great way to spend your valuable time, then please get in touch with us.

We are recruiting to fill the position below:

Job Title: Data Scientist - Financial Fraud Detection

Location: Lagos
Job type: Full time (Hybrid)

Job Overview

• We are seeking a highly skilled and experienced Data Scientist to join our Decision Science team, specializing in the development and deployment of advanced fraud detection models. 
• In this critical role, you will play a key part in safeguarding our customers and the bank from financial losses by identifying and mitigating fraudulent activities across various channels. 
• You will work with vast, complex transactional datasets, collaborate closely with Fraud Operation and Credit Risk and Compliance teams, and contribute to the continuous evolution of our fraud prevention strategies in a highly regulated environment.

Roles and Responsbilites

• Design, develop, and implement machine learning models tailored for banking fraud detection, including  anomaly detection, transaction fraud, account takeover, application fraud, and money laundering detection.
• Deploy and monitor real-time fraud detection systems, ensuring high performance and minimal latency.
• Continuously evaluate and refine models to improve accuracy and efficiency.
• Develop models that adhere to regulatory requirements and compliance standards (e.g., AML, KYC).
• Adapt models to the ever-changing tactics of financial criminals.
• Analyze large volumes of transactional data, customer behavior data, and external data sources to identify fraud patterns and anomalies.
• Conduct in-depth analysis of financial transactions to detect suspicious activities and potential fraud risks.
• Develop and maintain data pipelines for fraud-related data, ensuring data integrity and compliance.
• Collaborate with fraud investigators, risk managers, compliance officers, and technology teams to develop and implement effective fraud prevention solutions.
• Communicate complex model insights and fraud trends to stakeholders, including senior management and regulatory bodies.
• Participate in cross-functional projects related to financial crime prevention and risk management.
• Stay abreast of emerging fraud trends and regulatory changes in the banking industry.
• Research and evaluate new machine learning techniques and technologies for fraud detection in the financial sector.
• Contribute to the development of innovative solutions for combating financial crime.

Requirements

• Degree in Computer Science, Statistics, Mathematics, Finance, or a related quantitative field.
• A Master's or Ph.D. degree is desirable but not required.
• Minimum of 3 years of experience as a data scientist, within the banking or financial services industry.
• Proven experience in developing and deploying machine learning models for transaction monitoring, customer behaviour.
• Familiarity with Credit Product construct.
• Familiarity with regulatory requirements and compliance standards related to financial crime (e.g., AML, KYC, GDPR).
• Strong proficiency in Python and relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Expertise in SQL and experience with large-scale relational databases.
• Experience with fraud detection platforms and tools is desirable
• Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop).
• Knowledge of statistical analysis, time series analysis, and network analysis.
• Strong analytical and problem-solving skills, with a focus on detail and accuracy.
• Excellent communication and presentation skills, with the ability to convey complex information to diverse audiences.
• Ability to work effectively in a fast-paced, regulated environment.
• Strong understanding of banking operations and financial products.

Benefits
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.

Application Closing Date
Not Specified.