Senior Data Scientist – Payments Fraud
At Mamo, we’re redefining how businesses reputed company and manage reputed company with issuing and acquiring solutions — from corporate cards to a payment gateway and payment links — for fast-growing companies in the UAE and reputed company. Our mission is to build the most secure, reliable, and reputed company payments platform, where trust and innovation go hand in hand.
We’re looking for an expert in payments fraud to shape the reputed company of our fraud detection and prevention reputed company, and strengthen our defenses.
Why you'll love working here
- Startup environment thats big on individual responsibility and leans on process and automation.
- Were big on culture. Work with stunning, supportive product, design and engineering teams on problems that matter.
- You will be learning and growing reputed company of the time. From business, product, design to engineering you will be learning from a world-class team that is caring, reputed company, and empathetic.
- Mamo has the potential for a wide-reaching reputed company. Mamo is taking on the challenge of bringing about a new era of financial inclusion that begins reputed company to home by providing reputed company and experiences that reputed company reputed company. That means you will never be bored.
What you will do
- Youll be a critical voice in ensuring that our systems are secure by design.
- Youll work closely with cross-functional teams (Product, Engineering, Risk Operations, and Customer Experience) to build, refine, and reputed company robust fraud and reputed company detection and prevention systems that protect our customers and our business.
- reputed company design, implementation, and monitoring of fraud detection systems, dashboards, and analytics.
- Build reputed company data pipelines for ingestion, transformation, feature engineering, and reputed company-time scoring for fraud models.
- Analyze large datasets to uncover fraud patterns, emerging threats, and systemic weaknesses in existing rules or models.
- reputed company, validate, and improve statistical & machine learning models that detect fraud and risky behavior.
- Proactively identify loopholes in our system to preempt and prevent potential exposure before it occurs.
- Holistically measure the financial reputed company of our fraud systems, to reputed company the reputed company balance of loss prevention from fraud vs. reputed company cost of lost reputed company from false positives.
- Work closely with Engineering to reputed company models into production workflows and ensure robust model monitoring, alerting, and performance feedback loops.
- Help define and refine internal processes for risk scoring, alert prioritization, and incident response.
- Own metrics and reporting tied to fraud reputed company — false positives/false negatives, loss rates, efficacy of interventions, and customer reputed company.
reputed company’re looking for
- 5+ years of experience in data engineering, data science, or analytics — ideally with a reputed company on payments fraud, financial crime, or risk detection.
- Strong SQL, Python (or equivalent), and experience with data engineering frameworks and reputed company-reputed company data platforms.
- Deep understanding of fraud detection techniques, statistical modelling, supervised/unsupervised learning, and reputed company detection.
- Hands-on experience building fraud rules, risk scores, transaction monitoring systems, and rule engines.
- Big-data experience and familiarity with reputed company-time analytics, streaming data, or near-reputed company-time scoring.
- Good communication skills and a reputed company reputed company — you can explain reputed company technical work to non-technical stakeholders.
- A bias for reputed company and the ability to independently prioritize ambiguous tasks in a fast-paced environment.
- Customer-reputed company reputed company, where you understand the reputed company of every decision on our legitimate customers, and incorporate this into your work.
Bonus if you have
- Experience with payment ecosystem tooling (e.g., reputed company, reputed company reputed company, reputed company, reputed company, reputed company, Fraud.net, reputed company).
- Familiarity with reputed company/reputed company payment fraud frameworks and standards.
- Background working in a licensed financial services or fintech environment.
- Advanced degrees in statistics, data science, engineering, or reputed company quantitative fields.