Customer Support Systems & Analytics Lead

Remote from
USA, Canada
Salary, yearly, USD
138,800 - 192,800
Employment type
Full Time,
Job posted
Apply before
8 Aug 2026
Experience level
Senior
Views / Applies
24 / 0

About Mercury

Banking for startups: mercury.com

Actively Hiring
Verified job posting
This job post has been manually reviewed for authenticity and compliance.

AI Summary

This role is responsible for owning the data strategy and reporting function within the Customer Support organization at Mercury. The lead will manage data capture, structure, and connectivity across systems like Zendesk and an AI chatbot to drive informed decision-making. Key responsibilities include building dashboards, ensuring data quality, and translating insights into actionable recommendations for leadership. The ideal candidate has 5-8 years of experience in data analysis or systems analysis, with expertise in Zendesk administration, SQL, and BI tools. This position sits at the intersection of data, operations, and customer experience, requiring strong collaboration with cross-functional teams.

Role DNA

Job Complexity
Easy Hard
Pace & Pressure
Relaxed Fast-paced
Autonomy Level
Guided Full Ownership
Communication Load
Independent Highly Collaborative
AI Insight This role is rated difficulty 4 because it requires deep expertise in both technical systems (Zendesk, SQL, BI tools) and analytical skills, along with the ability to lead data strategy and communicate insights to stakeholders.

Salary Analysis

Median Highly Competitive
USD165,800
US Market
USD120k – 200k
0 USD220k
AI Insight The offered salary range of $138,800 - $192,800 is competitive for a lead-level Customer Support Systems & Analytics role in the US market, with the midpoint around $165,800. This reflects the technical expertise, leadership, and strategic impact required for the position.

Dear Hiring Manager,

I am excited to apply for the Customer Support Systems & Analytics Lead position at Mercury. With over 6 years of experience in data analytics and Zendesk administration, I have a strong track record of building scalable reporting infrastructure that drives operational efficiency. I am particularly drawn to this role because it combines my passion for data-driven decision-making with the challenge of optimizing customer support operations. My background in SQL, BI tools, and cross-functional collaboration aligns perfectly with the requirements. I look forward to contributing to Mercury's mission.

Sincerely, [Your Name]

How would you ensure data quality across Zendesk and other systems?
I would implement strict data governance standards, perform regular audits, and work with system admins to configure fields and triggers that enforce data consistency. Additionally, I would establish documentation and training to ensure all team members understand data entry requirements.
Describe your experience with building dashboards for non-technical stakeholders.
In my previous role, I built a suite of dashboards in Metabase that tracked key metrics like CSAT, response time, and resolution rate. I used clear visualizations and provided written explanations to ensure stakeholders could easily interpret the data. I also held regular review sessions to gather feedback and iterate on the dashboards.
How do you approach turning raw data into actionable insights?
I start by understanding the business question, then I clean and structure the data, perform exploratory analysis, and finally present findings with recommendations. I always validate insights with stakeholders to ensure they are practical and align with strategic goals.
What is your experience with Zendesk administration and reporting?
I have configured Zendesk to capture the right data fields, set up triggers for automation, and used Zendesk Analytics to build reports on ticket volumes, SLAs, and agent performance. I am also familiar with the API for custom integrations and have experience migrating data between systems.
Can you give an example of a time you improved a reporting process?
At my last job, our CS team relied on manual Excel reports. I automated the process by connecting Zendesk to a SQL database and built a live dashboard that reduced reporting time by 80% and improved data accuracy. This allowed the team to focus on analysis rather than data collection.

We’re looking for a Customer Support Systems & 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.

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.

 

Key Responsibilities

  • 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 – from our internal Support team to our BPO partners. 
  • 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.
  • Data hygiene standards: Define and enforce standards for how data is captured across CS systems so that reporting is accurate, trustworthy, and reproducible
  • 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
  • Insights to action: Translate raw data and reporting into clear recommendations that help CS leadership make decisions on resourcing, tooling, process improvements, and strategy
  • 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
  • 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
  • Process documentation: Document data structures, reporting methodologies, and system configurations to ensure institutional knowledge is retained and accessible across the team

What You Bring to the Table

  • 5-8 years of experience in a data analyst, business intelligence, or systems analyst role, ideally within a customer support or operations environment
  • 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
  • Fluency in SQL and experience working with data and BI tools such as Omni, Metabase, or similar
  • Strong analytical thinking with the ability to turn complex datasets into clear, actionable insights
  • Experience building and maintaining dashboards and reports for non-technical stakeholders
  • Deep understanding of data hygiene principles and how system configuration impacts data quality
  • Excellent communication skills, with the ability to present data findings clearly to stakeholders at all levels
  • Collaborative mindset with experience working cross-functionally across teams such as Operations, Product, and Engineering

The Ideal Candidate Will Also Have

  • Experience working with AI chatbot or conversational analytics platforms
  • Familiarity with other CS tools such as Intercom, Guru, or Rippit (formerly known as MaestroQA)
  • Experience working in a high-growth SaaS or fintech environment
  • Background in supporting data-driven workforce planning or CS strategy initiatives

 

The total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits.

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.

Our target new hire base salary ranges for this role are the following:

  • US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $154,200 – $192,800
  • US employees outside of New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $138,800 – $173,500
  • Canadian employees (any location): CAD $145,800 – $182,200

 

Mercury values diversity & 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.

#LI-AS1

 

Apply now >

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