Role Overview
As a Data Analyst within Customer Identity Shared Services, you will be instrumental in driving improvements to customer identity management systems, ensuring secure and efficient customer experiences. Utilizing data analytics and a hypothesis-driven test-and-learn approach, your focus will be on optimizing identity verification processes, enhancing customer authentication journeys, and supporting the overall framework of shared services in customer identity management.
Working within cross-functional teams, you will create valuable insights into the effectiveness of current identity strategies, identify key opportunities for enhancement, and develop business cases and testing plans to execute on those opportunities.
You will expand your competencies in customer identity management technologies, grow your business and industry acumen, and demonstrate your ability to manage complex projects across their lifecycle. Additionally, you will contribute innovative solutions to identity management challenges, helping to refine and push the boundaries of our shared services in this domain.
Key Responsibilities
- Data Analysis & Strategy Design: Extract, analyze, and interpret customer identity data from multiple systems to design, recommend, and execute strategies for customer identity shared services. Utilize tools such as SQL, Heap, Python, Snowflake and R to develop, test, and optimize customer segmentation schemes and authentication strategies.
- Model Development: Apply traditional regression models and machine learning algorithms to understand the drivers of customer behavior in relation to identity management, estimating the impact of different strategies on security and customer experience.
- Cross-Functional Collaboration: Work closely with IT, security, and product teams to ensure that customer identity shared services align with broader business goals and customer needs.
- Insight Communication: Effectively summarize and present data-driven insights and results to senior management and stakeholders to inform decision-making and drive strategic initiatives.
- Quality Control & Process Improvement: Implement quality control processes to ensure data accuracy and integrity. Continually enhance existing identity management processes and reporting through automation, quality control measures, and insightful presentations.
Requirements
- Educational Background: Bachelor’s degree (Graduate degree preferred) in a quantitative discipline such as Engineering, Statistics, Economics, Computer Science, or a related field and 5+ years of relevant analytical experience.
- Technical Skills: Strong proficiency in SQL, Python, and Excel; experience with customer identity management platform such as OKTA, multiple types of relational databases, BI tools, and/or additional programming languages is a plus.
- Experience: 4-5 years of experience in a complex, data-driven problem-solving environment
- Problem-Solving: Demonstrated ability to apply a highly analytical approach to complex problems, with a focus on identity management and customer experience.
- Industry Knowledge: Experience in identity management, cybersecurity, or consumer finance industries is preferred.