Lead Systems Data Analyst - Regulatory Compliance Monitoring, Investments, Data Governance

Are you a data visionary with a passion for the complexities of the investment world? Yoh, a Day & Zimmermann Company, is seeking a Lead Systems Data Analyst to join our high-impact Data & Analytics team. This is a unique opportunity to bridge the gap between technical architecture and regulatory strategy, where you will take ownership of the data lifecycle within a sophisticated asset management environment. If you thrive on solving complex puzzles and want to play a pivotal role in ensuring our compliance frameworks are as robust as our data models, we want to hear from you.

In this dynamic, 100% remote role, you will be the architectural backbone of our regulatory compliance monitoring initiatives. You will leverage your technical proficiency in SQL, Python, and advanced data modeling to design seamless data mappings and orchestrate the flow of information across our systems. We aren't just looking for someone to push data; we are looking for a strategic thinker who understands the "why" behind every integration. You will have the autonomy to shape how we govern our data assets, ensuring complete accuracy and transparency while contributing to the success of our global investment operations.

We invite you to bring your analytical curiosity and technical expertise to a company where your work directly influences high-stakes financial decisions. By joining the Yoh team, you are positioning yourself at the intersection of cutting-edge data governance and institutional finance. If you are ready to elevate your career by mastering the intricacies of compliance data in a remote-first, collaborative environment, apply today to start your journey with us.

Requirements

• Strong proficiency in SQL and data visualization tools (Tableau, PowerBI).
• Experience with statistical programming languages like R or Python.
• Ability to derive actionable insights from large, complex datasets.
• Strong mathematical background and analytical thinking.
• Experience with data warehousing and ETL processes is beneficial.
• Degree in Statistics, Mathematics, Economics, or a related field.