Who We Are

Join a team that puts its People First! As a member of First American's family of companies, National Commercial Services provides single-point service for simple to multi-property/multi-state national commercial real estate transactions. Since 1889, First American (NYSE: FAF) has held an unwavering belief in its people. They are passionate about what they do, and we are equally passionate about fostering an environment where all feel welcome, supported, and empowered to be innovative and reach their full potential. Our inclusive, people-first culture has earned our company numerous accolades, including being named to the Fortune 100 Best Companies to Work For® list for ten consecutive years. We have also earned awards as a best place to work for women, diversity and LGBTQ+ employees, and have been included on more than 50 regional best places to work lists. First American will always strive to be a great place to work, for all. For more information, please visit www.careers.firstam.com.

What We Do

We are seeking a hands-on, results-driven leader to elevate our reporting and analytics capabilities. As Sr Manager of Data Analytics & Insights, you will lead a team responsible for designing, developing, and optimizing analytics solutions that drive business impact. You will serve as both a technical contributor and people leader—mentoring team members, promoting best practices, and fostering a culture of innovation and continuous improvement.

Team Leadership & Development

• Directly manage, mentor, and develop a team of analytics and reporting professionals.
• Set clear expectations, goals, and accountabilities for team members.
• Conduct regular 1:1s, provide feedback, and support career growth.
• Promote a collaborative, high-performing team environment.

Technical Execution & Delivery

• Oversee the design, development, and maintenance of analytics dashboards, data pipelines, and advanced analytics solutions.
• Serve as a technical expert, contributing hands-on to complex analytics projects as needed.
• Champion the integration of AI/ML and automation into analytics workflows, in partnership with Data Engineering.

Analytics & Insights

• Translate business needs into actionable analytics solutions and insights.
• Promote self-service analytics and data democratization across the organization.
• Ensure data visualizations and dashboards are clear, compelling, and actionable.

Data Quality & Governance

• Ensure high standards of data quality, accuracy, and security in all analytics outputs.
• Collaborate with Data Engineering to optimize data models and pipelines for analytics use.

Stakeholder Engagement

• Partner with business stakeholders to understand requirements, prioritize analytics initiatives, and communicate findings.
• Present complex analytics in a clear, concise manner, translating insights into actionable recommendations.

Process Improvement & Efficiency

• Identify and implement opportunities to automate and improve analytics processes.
• Continuously enhance the scalability, efficiency, and reliability of analytics operations.

Technology & Tooling

• Evaluate and implement modern BI, analytics, and AI platforms in alignment with team and business needs.
• Stay current on industry trends and emerging technologies; recommend adoption where appropriate.

Change Management & Adoption

• Drive adoption of new analytics solutions within the business.
• Lead training and enablement initiatives to maximize the impact and utilization of analytics tools and outputs.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Business Analytics, or a related field (Master’s preferred).
• 7+ years of experience in data analytics, BI, or data science roles, with at least 2 years in a people management capacity.
• Demonstrated hands-on experience integrating AI/ML into analytics and reporting environments.
• Proficiency in at least one analytics programming language (e.g., Python, R, SQL).
• Strong expertise with BI tools (e.g., Power BI, Tableau, Looker, Domo) and data visualization best practices.
• Experience building and deploying data pipelines (ETL/ELT), preferably with cloud data platforms (e.g., AWS, Azure, GCP).
• Solid understanding of data engineering, data governance, and data quality concepts.
• Proven ability to translate business needs into actionable analytics and insights.
• Excellent communication and stakeholder management skill