Senior Manager of Data Analytics, Mission Lane

• Have 7+ years of data analysis experience with a high level of proficiency in SQL (complex joins, window functions, etc) to extract insights from large datasets
• Have 5+ years of experience driving analytical outcomes leveraging business intelligence tools (Tableau, Looker, Mode, etc)
• Have 3+ years of experience serving as a people manager for an analyst team
• Previous experience leveraging Data Build Tool (dbt) or equivalent tool to develop analytical data products for consumption across an organization
• Manage projects across multiple stakeholders and prioritize vigilantly
• Incorporate data management best practices and standards to deliver high quality data deliverables
• Use dimensional data modeling and analytics engineering best practices that enable robust analysis on datasets you and your team develop and own

Desirable

• We’re seeking a strategic and experienced leader in data analytics, business intelligence, and analytics engineering to join our Data Science team as a Senior Manager of Data Analytics
• In this critical role, you will drive the development and execution of advanced data solutions that power decision-making across the enterprise, creating meaningful value for our customers
• Your expertise will shape Mission Lane’s data strategy, enhancing analytics capabilities, business intelligence, and data engineering processes
• You'll have the opportunity to directly influence the company’s growth and culture, leveraging data to improve decision quality
• As we work toward becoming a household name in financial products, your contributions will help serve the 50% of Americans traditionally overlooked by financial institutions
• Driving our analytic strategies forward as a hands-on manager, diving into our most challenging data analysis questions across the business
• Applying deep expertise in business intelligence, data analysis, and analytics engineering to create and analyze large volumes of data as well as enable accurate, fast usage across the enterprise
• Incorporating software development best practices into your team’s workflows, ensuring that analysis being executed is of high quality, scalable, and meets partner needs
• Collaborating with data science, engineering, product management, and business partner teams within the organization to highlight opportunities for data to drive project initiatives forward
• Making your team better on a daily basis because you can be clear about goals, the team’s shared purpose, and need to execute through education, organization, and trust