In partnership with our client we are seeking a Data Science Manager (Fraud) who understands that behind every transaction is a real persons financial life and knows how to protect it. This is a role for someone who combines deep technical expertise with sharp strategic thinking leading a team that builds the fraud detection and prevention systems that keep millions of customers safe. You will own the roadmap architect real-time decision systems and stay one step ahead of financial crime in a fast-growing global fintech. If you are energised by the intersection of data science fraud risk and genuine human impact we want to meet you.
Who are we looking for
- You are a systems thinker someone who sees the hidden patterns in massive datasets and knows how to turn those patterns into scalable intelligent defences.
- You are deeply technical with hands-on expertise in machine learning fraud modelling and high-volume transactional data but you never lose sight of the bigger picture.
- You are a natural communicator who can translate complex analyses into clear compelling stories that resonate with engineers product teams and business leaders alike.
- You are a leader who invests in people someone who mentors with intention creates space for growth and builds cultures of mastery and accountability.
- You are gritty and adaptable comfortable navigating ambiguity in a fast-moving scale-up and driving momentum even when the path isnt fully paved.
- You are human-centric at your core. You understand that behind every data point is a real persons financial happiness and that drives everything you do.
Your Responsibilities
Strategy and amp; Vision
- You will build and own the roadmap for fraud decisioning ensuring our models stay ahead of emerging fraud typologies and financial crime trends.
- You will set the direction for customer screening transaction monitoring and authentication designing systems that grow with the business.
Technical Leadership
- You will develop and refine fraud scoring methodologies building features from high-volume transactional device and behavioural data.
- You will design and deploy real-time decision logic and data architectures in close partnership with Product and Engineering teams.
- You will build test and scale machine learning models that maintain a world-class balance between fraud detection precision and recall.
- You will design and run experiments including A/B tests to continuously improve model performance without adding unnecessary friction for honest users.
Governance and amp; Monitoring
- You will ensure data quality and responsible model usage within our regulated environments keeping compliance front and centre.
- You will monitor model performance and drift consistently evolving our defences as fast as the threats do.
- You will maintain thorough documentation of models and processes ensuring transparency and auditability.
People and amp; Collaboration
- You will lead mentor and develop a team of data scientists fostering a culture of continuous learning technical excellence and psychological safety.
- You will collaborate cross-functionally with Product Engineering and Business stakeholders to embed fraud logic seamlessly into our products.
What Success looks like
- Fraud detection systems maintain a world-class precision-recall balance with measurable reduction in fraud losses over time.
- Fraud decision logic is fully integrated into our products with minimal friction to genuine users measured by customer experience scores and false positive rates.
- At least 80% of team members report clarity on their growth path and feel empowered to do their best work.
- All models are documented compliant and consistently monitored with zero material compliance incidents related to model governance.
- Experimentation is embedded into the teams workflow with a regular cadence of tests driving measurable improvements in fraud outcomes.
To be considered for this role you should have
- 6 years of experience in Data Science Decision Science or Fraud Risk ideally within financial services.
- A degree or equivalent experience in a quantitative field such as Statistics Mathematics Engineering or similar.
- Deep knowledge of fraud typologies financial crime and the relevant regulatory landscape.
- Strong proficiency in SQL and Python (our primary programming language).
- Demonstrated success building and deploying machine learning models at scale in production environments.
- Experience leading or mentoring technical teams in fast-paced high-growth settings.
- Preferred: Experience with A/B testing and experimentation in real-time environments.
- Preferred: Familiarity with churn management and user retention modelling.
- Preferred: An advanced degree (MSc or PhD) in a related quantitative field.
Challenges you may face in this role
- Staying ahead of sophisticated and constantly evolving fraud patterns in a rapidly scaling product environment.
- Balancing the tension between robust fraud prevention and a frictionless user experience tightening security without punishing honest customers.
- Building and maintaining model integrity within a regulated financial services environment where compliance requirements add layers of complexity.
- Leading a technical team remotely while fostering a strong culture of collaboration accountability and continuous growth.
- Operating with ambiguity in a high-growth scale-up where priorities shift quickly and the pace of change is relentless.
The Goodies
- Competitive salary with pension health insurance and an annual performance bonus.
- A people-first culture where all voices are genuinely heard and valued.
- A rich learning environment with regular technical talks knowledge-sharing sessions and a strong focus on professional development.
- The opportunity to do meaningful work that protects the financial lives of millions of people across Africa and beyond.
In partnership with our client we are seeking a Data Science Manager (Fraud) who understands that behind every transaction is a real persons financial life and knows how to protect it. This is a role for someone who combines deep technical expertise with sharp strategic thinking leading a team that ...
In partnership with our client we are seeking a Data Science Manager (Fraud) who understands that behind every transaction is a real persons financial life and knows how to protect it. This is a role for someone who combines deep technical expertise with sharp strategic thinking leading a team that builds the fraud detection and prevention systems that keep millions of customers safe. You will own the roadmap architect real-time decision systems and stay one step ahead of financial crime in a fast-growing global fintech. If you are energised by the intersection of data science fraud risk and genuine human impact we want to meet you.
Who are we looking for
- You are a systems thinker someone who sees the hidden patterns in massive datasets and knows how to turn those patterns into scalable intelligent defences.
- You are deeply technical with hands-on expertise in machine learning fraud modelling and high-volume transactional data but you never lose sight of the bigger picture.
- You are a natural communicator who can translate complex analyses into clear compelling stories that resonate with engineers product teams and business leaders alike.
- You are a leader who invests in people someone who mentors with intention creates space for growth and builds cultures of mastery and accountability.
- You are gritty and adaptable comfortable navigating ambiguity in a fast-moving scale-up and driving momentum even when the path isnt fully paved.
- You are human-centric at your core. You understand that behind every data point is a real persons financial happiness and that drives everything you do.
Your Responsibilities
Strategy and amp; Vision
- You will build and own the roadmap for fraud decisioning ensuring our models stay ahead of emerging fraud typologies and financial crime trends.
- You will set the direction for customer screening transaction monitoring and authentication designing systems that grow with the business.
Technical Leadership
- You will develop and refine fraud scoring methodologies building features from high-volume transactional device and behavioural data.
- You will design and deploy real-time decision logic and data architectures in close partnership with Product and Engineering teams.
- You will build test and scale machine learning models that maintain a world-class balance between fraud detection precision and recall.
- You will design and run experiments including A/B tests to continuously improve model performance without adding unnecessary friction for honest users.
Governance and amp; Monitoring
- You will ensure data quality and responsible model usage within our regulated environments keeping compliance front and centre.
- You will monitor model performance and drift consistently evolving our defences as fast as the threats do.
- You will maintain thorough documentation of models and processes ensuring transparency and auditability.
People and amp; Collaboration
- You will lead mentor and develop a team of data scientists fostering a culture of continuous learning technical excellence and psychological safety.
- You will collaborate cross-functionally with Product Engineering and Business stakeholders to embed fraud logic seamlessly into our products.
What Success looks like
- Fraud detection systems maintain a world-class precision-recall balance with measurable reduction in fraud losses over time.
- Fraud decision logic is fully integrated into our products with minimal friction to genuine users measured by customer experience scores and false positive rates.
- At least 80% of team members report clarity on their growth path and feel empowered to do their best work.
- All models are documented compliant and consistently monitored with zero material compliance incidents related to model governance.
- Experimentation is embedded into the teams workflow with a regular cadence of tests driving measurable improvements in fraud outcomes.
To be considered for this role you should have
- 6 years of experience in Data Science Decision Science or Fraud Risk ideally within financial services.
- A degree or equivalent experience in a quantitative field such as Statistics Mathematics Engineering or similar.
- Deep knowledge of fraud typologies financial crime and the relevant regulatory landscape.
- Strong proficiency in SQL and Python (our primary programming language).
- Demonstrated success building and deploying machine learning models at scale in production environments.
- Experience leading or mentoring technical teams in fast-paced high-growth settings.
- Preferred: Experience with A/B testing and experimentation in real-time environments.
- Preferred: Familiarity with churn management and user retention modelling.
- Preferred: An advanced degree (MSc or PhD) in a related quantitative field.
Challenges you may face in this role
- Staying ahead of sophisticated and constantly evolving fraud patterns in a rapidly scaling product environment.
- Balancing the tension between robust fraud prevention and a frictionless user experience tightening security without punishing honest customers.
- Building and maintaining model integrity within a regulated financial services environment where compliance requirements add layers of complexity.
- Leading a technical team remotely while fostering a strong culture of collaboration accountability and continuous growth.
- Operating with ambiguity in a high-growth scale-up where priorities shift quickly and the pace of change is relentless.
The Goodies
- Competitive salary with pension health insurance and an annual performance bonus.
- A people-first culture where all voices are genuinely heard and valued.
- A rich learning environment with regular technical talks knowledge-sharing sessions and a strong focus on professional development.
- The opportunity to do meaningful work that protects the financial lives of millions of people across Africa and beyond.
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