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Data Scientist
2 months ago
We are seeking a highly skilled Data Scientist to join our Fraud Data Science & Analytics team. As a key member of our team, you will be responsible for developing and optimizing fraud detection strategies to maximize operational effectiveness and minimize client impact.
Key Responsibilities- Identify patterns, trends, and hidden causation and correlation relationships from fraud data and advise the Fraud Management Senior Management Team of emerging trends, specific gaps, or systemic issues that impact the fraud risk of RBC.
- Collaborate with appropriate partners for action, correction, awareness, and training.
- Forecast financials and fraud KPIs using predictive analytics techniques and generate insights for executive decision-making and communicating results through insightful visualizations, white papers, reports, and presentations.
- Research business problems, develop solutions to support investigation and analysis, and lead the progression of analytics methodology, tools, and measurement to create development templates for automation.
- Build the foundation of information in consolidated data repositories for operations, fraud events, fraud performance, and financials.
- Provide a complete picture of the fraud landscape with drill-down capabilities for root cause analysis and deliver self-serve interactive visualizations through accessible platforms like Tableau.
- Conduct code reviews and develop standards for development practices and partner with project teams to support information required for analysis of the current state.
- Deliver project reporting for fraud events, performance, operational, and financial KPIs and KRI's and program benefits measurements to track success criteria of the project business case.
- 2+ years' experience in a data science and analytics role.
- Advanced capability in using Python, R, PySpark, SAS, SQL, and Tableau.
- Experience with databases and data structures (RDBMS, Hadoop, etc.).
- Ability to apply data and analytics concepts to business problems and explain the business value of data and analytics concepts.
- Ability to multi-task and prioritize and complete projects effectively and in a timely manner.
- Strong team player with a track record of collaboration and experience working as part of an agile team.
- Professional verbal and written communication and presentation skills, and ability to provide consultation, analysis, and recommendations on a broad range of projects in a deadline-driven environment with ambiguity.
- Fair compensation.
- Challenging work in a fast-paced timeline-driven work environment.
- Ability to make a difference and lasting impact.
- Work with a great and supportive team.
Base SAS, Big Data Management, Data Science, Decision Making, Hadoop Distributed File System (HDFS), Hadoop Ecosystem, Machine Learning, Predictive Analytics, PySpark, Python (Programming Language), Relational Database Development, R Programming, SAS Enterprise Guide, Statistical Analysis, Structured Query Language (SQL), Tableau (Software)