Staff Data Analyst

Facet was founded in 2016 on the belief that objective, personalized financial advice is essential to living well. Our mission is to empower people to live more enriched lives by delivering a new standard of advice. By removing asset minimums, we provide holistic planning that goes far beyond investments to address every way money impacts life. To achieve this, we leverage a "human-plus-tech" approach, combining the expertise of CFP professionals with cutting-edge AI and automation. This model allows Facet to integrate advice into our members' entire financial picture-all for an affordable, flat membership fee.

Our commitment to innovation and member success has earned national recognition, including being ranked the #1 Best Financial Advisory Firm 2025 by USA TODAY and named to Newsweek's list of America's Top Financial Advisory Firms 2025. With an A+ BBB Rating and a Trustpilot "Excellent" score (as of Sept. 16, 2025)*, we are proud to be redefining the industry for our members and our team alike.

The Role

As a Staff Data Analyst at Facet, you will lead efforts to equip Facet operations, product, and leadership teams with the high-impact insights they need to maximize business performance. You will join the Data Science & Analytics team tasked with modeling, understanding, and optimizing various aspects of our growth, margin, and retention initiatives. This is not a traditional BI or dashboard-building role-you will not spend your days drag-and-dropping in legacy BI systems. Instead, you will act as a high-influence strategic partner and advisor to our executive management and senior leadership teams.

You should be an expert in using Python and SQL to build lightweight, highly actionable data reporting tools (using Streamlit and BigQuery-connected Google Sheets) and conducting deep-dive Exploratory Data Analysis (EDA) in Jupyter Notebooks. Additionally, you will be expected to leverage and integrate modern, secure AI-assisted engineering tools and workflow automation to exponentially scale the speed, accuracy, and depth of your analytical processes.

The perfect candidate is a proactive value-hunter who enjoys embedding themselves in cross-functional teams, has exemplary interpersonal and stakeholder management skills, and loves translating complex analytical insights into clear, strategic business recommendations.

Day-To-Day Responsibilities

• Be a Trusted Strategic Advisor: Act as a direct analytical partner to senior leadership and executive management. You will spend a significant portion of your day in an advisory role, translating complex data findings into clear, leadership-level recommendations and partnering across business units to drive changes in strategy.
• Proactive Value Capture: Do not wait for questions to be asked. You will proactively hunt for opportunities to optimize business performance, increase efficiency, and capture untapped value, then work hand-in-hand with teams across the organization to execute on those opportunities.
• Rapid, Scripted Analytics & EDA: Perform deep-dive Exploratory Data Analysis (EDA) using Jupyter Notebooks to diagnose business trends, test complex hypotheses, and discover hidden relationships in our data.
• Modern Interactive Reporting: Build and maintain streamlined, interactive data tools using Python and Streamlit, and design high-impact, BigQuery-connected Google Sheets to deliver self-service data directly into the workflows of business leaders.
• Analytical Workflow Automation & AI Integration: Actively integrate modern AI assistant technologies and secure automation practices into your day-to-day analytics workflows. You will utilize model-driven tools to accelerate code generation, optimize SQL queries, and automate repetitive data exploration tasks safely and efficiently.
• Data Assembly & Quality: Gather, clean, and model data from various sources using optimized Python, SQL, and dbt, ensuring absolute consistency and accuracy.
• Evaluate & Produce Quality: Ensure the integrity of our analytical output. You will participate in peer reviews of SQL queries, Python scripts, and analytical methodologies to keep our standards high.