Data Science Manager (Fraud)

Actively Reviewing the Applications

CareerBuddy

India, Karnataka, Bengaluru Full-Time On-site

Posted 9 hours ago • Apply by June 9, 2026

Job Description

In partnership with our client, we are seeking a Data Science Manager (Fraud) who understands that behind every transaction is a real person's 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 isn't fully paved.
You are human-centric at your core. You understand that behind every data point is a real person's financial happiness, and that drives everything you do.

Your Responsibilities...

Strategy & 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 & 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 & 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 team's 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.