Data Analyst - Risk & Fraud

SUMMARY:

POSITION INFO:
The Data Analyst will be responsible for:

• Data Acquisition and Integration
• Collaborated with stakeholders to understand data needs and requirements
• Developed and implemented strategies for acquiring data from various sources, including internal databases
• Ensured data quality and consistency through cleaning, transformation, and validation processes
• Data Analysis and Interpretation
• Designed and executed queries using SQL to extract and manipulate data from relational databases
• Utilised Python and Pyspark for advanced data manipulation, statistical analysis, and machine learning tasks
• Conducted in-depth analysis of data to identify trends, patterns, and anomalies
• Translated complex data findings into actionable insights and recommendations
• Data Visualization and Communication
• Developed clear and concise data visualisations using Power BI to effectively communicate insights to a broad audience
• Created dashboards and reports to track key performance indicators (KPIs) and monitor business performance
• Presented data findings and recommendations to stakeholders in a clear, compelling, and easy-to-understand manner
• Participated in discussions and meetings to provide data-driven insights and support decision-making processes

• Proven experience with Power BI for data visualisation and reporting
• Proficiency in SQL for querying and manipulating data from relational databases
• Experience working with Pandas, Scikit Learn, and Pyspark
• Experience with Git version control system
• Familiarity with data analysis methodologies, statistical concepts, and machine learning fundamentals
• Familiarity with Graph Theory, Social network analysis, and Link Analysis
• Working knowledge of AWS Neptune DB, Graph Explorer, and Gremlin is an advantage

• Minimum 5 years experience in a Data Analyst role with at least 3 years experience in advanced analytics
• Bachelor's degree in a relevant field such as statistics, computer science, mathematics, engineering, or business (or equivalent experience)
• Strong analytical and problem-solving skills with a keen eye for detail
• Excellent communication and presentation skills, both written and verbal
• Ability to work independently and manage multiple tasks effectively
• Strong teamwork and collaboration skills