Senior Data Analyst - Anti-Fraud/AML/BI Track
About Mox
Mox is built by and for the ones who aspire to live life to the fullest – we call them Generation Mox! The name Mox reflects the endless opportunities we can create, - Mobile eXperience; Money eXperience; Money X (multiplier), eXponential growth, eXploration… it’s all up for us to define together.
Why Mox
Everything at Mox – from our products, features, to rewards – is designed based on customer research, tailor made for your needs. We care about what customers care about, especially in data security and privacy. Data ethics is core to everyone here at Mox. Mox rewards you with an array of banking and lifestyle benefits. Who says banking can’t be fun?
Who are we looking for?
We are seeking a highly analytical and experienced Senior Data Analyst. In this pivotal role, you will be responsible for transforming complex data into actionable insights that directly influence our risk management, fraud prevention, operational efficiency and customer experience. The ideal candidate is a problem-solver who thrives in a collaborative environment and is passionate about using data to drive strategic decisions in the financial sector.
- Dashboard & Reporting: Design, build, and maintain interactive dashboards and recurring reports to monitor key business performance indicators and risk trends for stakeholders across the organization.
- Exploratory Analysis: Conduct deep-dive, explorative analysis using advanced data and statistical modeling techniques to uncover root causes, identify opportunities, and answer critical business questions.
- Risk Strategy Optimization: Proactively analyze and optimize the performance of our anti-fraud and Anti-Money Laundering (AML) engines to improve control effectiveness, reduce false positives, and enhance operational efficiency.
- Process Improvement: Leverage data to identify bottlenecks and opportunities for optimization within internal operational processes, recommending data-driven solutions for improvement.
- Business Impact Sizing: Quantify the potential impact, value, and ROI of proposed business initiatives and requirements to inform prioritization and strategic planning.
- Cross-Functional Collaboration: Work closely with Product Managers, Engineers, and business stakeholders to define requirements, develop data-driven solutions, and ensure successful deployment and adoption.
- Education: An advanced degree (Master's or above) in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Engineering, or Economics.
- Experience:
- 1-5 years of hands-on experience in a data analytics role, with a proven track record of delivering business impact.
- Experience within a financial services, banking, or payment institution is highly preferred.
- Practical experience in risk analytics, fraud analysis, or AML is a significant advantage.
- Technical Proficiency:
- Expert proficiency in SQL and Hive for extracting and manipulating large datasets.
- Strong programming skills in Python (e.g., Pandas, NumPy, Scikit-learn) for data analysis and modeling.
- Extensive experience processing and analyzing large-scale datasets.
- Proficiency with data visualization tools such as Tableau, Power BI
- Preferred Skills:
- Experience with statistical analysis and machine learning techniques (e.g., regression, classification, clustering) is a strong plus.
- Familiarity with big data technologies (Spark, Hadoop) is desirable.
- Soft Skills:
- Excellent communication and storytelling skills, with the ability to translate complex technical findings into clear, actionable recommendations for non-technical audiences.
- Strong business acumen and a keen interest in the financial industry.
- A proactive, self-starter attitude with the ability to manage multiple projects in a fast-paced environment.