Customer Support Systems & Analytics Lead

Sobre el puesto

<p>We’re looking for a Customer Support Systems &amp; Analytics Lead to own the data strategy and reporting function within the Customer Support organisation at Mercury. As our operations grow in complexity—spanning multiple channels, an expanding BPO model, and sophisticated AI automation—we are moving away from fragmented, project-based data support toward a model of holistic ownership.</p> <p>In this role, you will be responsible for how we capture, structure, and connect data across our CS systems - including Zendesk and our AI Agent - to drive informed decision-making across the team. You will ensure our systems are configured in a way that produces reliable, high-quality data, and you will translate that data into actionable insights for CS leadership and stakeholders. You’ll sit at the intersection of data, operations, and customer experience, partnering closely with CS leadership, Strategy and Ops, and cross-functional teams like Data to make sure our reporting infrastructure is built to scale. Your work will be foundational to how the CS organisation measures performance, identifies opportunities, and drives decision-making.</p> <p>&nbsp;</p> <h3>Key Responsibilities</h3> <ul> <li>Unified reporting and analytics: Actively build and maintain reports and dashboards that give the CS organisation clear visibility into key performance metrics, trends, and performance across channels, teams and projects&nbsp; - from our internal Support team to our BPO partners.&nbsp;</li> <li>CS Systems configuration and data governance: Work closely with systems admins to advise on the structural setup of our Zendesk instance across customer-facing teams, ensuring it is configured to generate clean, consistent, and reliable data while maintaining secure systems and efficient workflows.</li> <li>Data hygiene standards: Define and enforce standards for how data is captured across CS systems so that reporting is accurate, trustworthy, and reproducible</li> <li>AI automation data oversight: Monitor and analyse data from our AI chatbot, ensuring it is tracked in a way that supports quality reviews and decision-making across the CS organisation</li> <li>Insights to action: Translate raw data and reporting into clear recommendations that help CS leadership make decisions on resourcing, tooling, process improvements, and strategy</li> <li>Stakeholder support: Partner with cross-functional partners in areas like Product, Data and Strategic Finance to understand their data needs and deliver reporting that supports their goals</li> <li>Systems evaluation: Assess the data capabilities of existing and new CS tools, and make recommendations on how to optimise our systems stack for better reporting outcomes</li> <li>Process documentation: Document data structures, reporting methodologies, and system configurations to ensure institutional knowledge is retained and accessible across the team</li> </ul> <h3>What You Bring to the Table</h3> <ul> <li>5-8 years of experience in a data analyst, business intelligence, or systems analyst role, ideally within a customer support or operations environment</li> <li>Hands-on experience with Zendesk administration and configuration, including views, fields, triggers, and reporting, as well as using Zendesk Analytics to build reports and dashboards</li> <li>Fluency in SQL and experience working with data and BI tools such as Omni, Metabase, or similar</li> <li>Strong analytical thinking with the ability to turn complex datasets into clear, actionable insights</li> <li>Experience building and maintaining dashboards and reports for non-technical stakeholders</li> <li>Deep understanding of data hygiene principles and how system configuration impacts data quality</li> <li>Excellent communication skills, with the ability to present data findings clearly to stakeholders at all levels</li> <li>Collaborative mindset with experience working cross-functionally across teams such as Operations, Product, and Engineering</li> </ul> <h3>The Ideal Candidate Will Also Have</h3> <ul> <li>Experience working with AI chatbot or conversational analytics platforms</li> <li>Familiarity with other CS tools such as Intercom, Guru, or Rippit (formerly known as MaestroQA)</li> <li>Experience working in a high-growth SaaS or fintech environment</li> <li>Background in supporting data-driven workforce planning or CS strategy initiatives</li> </ul> <p>&nbsp;</p> <p>The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.</p> <p>Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.</p> <h3><strong>Our target new hire base salary ranges for this role are the following:</strong></h3> <ul> <li>US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $154,200 - $192,800</li> <li>US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $138,800 - $173,500</li> <li>Canadian employees (any location): CAD $145,800 - $182,200</li> </ul> <p>&nbsp;</p> <p>Mercury values diversity &amp; belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.</p> <p>#LI-AS1</p> <p>&nbsp;</p>