Senior Data Analyst

  • $80k – $100k • No equity
  • |Remote (
    Argentina • 
    +8)
  • |2 years of exp
  • |Full Time
Posted: today• Recruiter recently active
Hires remotely in
Remote Work Policy

Remote only

Company Location
Visa Sponsorship

Not Available

Preferred Timezones
Pacific Time
RelocationAllowed
Skills
Business Development
Data Analysis
Web Technologies
Data Management
LLM Frameworks (Langchain, Claude, LLamaIndex) RAG Technologies Embedding Models Vect
Hiring contact
Hina Lee
Employee
image

About the job

Senior Data Analyst

Team: Product & Data

Level: Senior Individual Contributor

Employment: Full-time

About Monoco

Monoco builds intelligent operating systems for ambitious businesses. We replace disconnected tools with software shaped around the way a company actually works—giving each business a system it can depend on, evolve, and own.

The role

We're looking for a Senior Data Analyst to make data a dependable part of how Monoco builds its product and runs the company. You will bring structure to questions across product usage, customer delivery, revenue, and internal operations—deciding what should be measured, building reliable ways to measure it, and turning the results into clear decisions.

At this stage, the work is equal parts analysis and foundation-building. One week you may define the metrics behind a company priority and build the reporting around it. The next, you may investigate an unexpected customer pattern, improve product instrumentation, or help a team separate a useful signal from an appealing but incomplete conclusion.

This role is a good fit for someone who enjoys hands-on analytical work, is comfortable with ambiguity, and wants meaningful influence over how an early-stage company uses data.

What you will do

  • Define and maintain the core metrics Monoco uses to understand product adoption, customer outcomes, commercial performance, and company operations.
  • Build well-structured data models, dashboards, and recurring reporting that teams can use without needing an analyst to interpret every number.
  • Analyze customer and product behavior to identify adoption patterns, friction points, retention risks, and opportunities to improve the experience.
  • Partner with product and engineering on event tracking, source data, metric logic, and the reliability of new instrumentation.
  • Investigate data-quality issues, reconcile conflicting numbers, and document the definitions and assumptions behind important reporting.
  • Support product tests and business initiatives with practical measurement plans, thoughtful analysis, and clear statements about uncertainty.
  • Turn one-off questions into reusable datasets, reporting, or analytical methods when the need is likely to recur.
  • Use AI tools to accelerate query development, documentation, and exploratory work while independently checking the code, logic, and conclusions.

What success looks like

  • Monoco has a small, trusted set of metrics that gives the team a shared view of product, customer, and business performance.
  • Leaders and functional owners can answer common questions through clear, dependable reporting instead of assembling numbers by hand.
  • Gaps in instrumentation and data quality are found early, assigned clearly, and resolved before they undermine important decisions.
  • Analysis leads to concrete changes in product priorities, customer delivery, or company operations—not simply more dashboards.

What we are looking for

  • Two or more years of experience in product analytics, business intelligence, growth analytics, or a closely related role.
  • Advanced SQL skills and experience working with a modern data warehouse and business-intelligence platform.
  • A practical understanding of data modeling, metric design, cohort analysis, experimentation, and statistical reasoning.
  • Working proficiency in Python or R for analyses that extend beyond SQL and standard reporting.
  • The ability to take an ambiguous business question, define the analytical approach, and communicate a useful answer to both technical and non-technical teammates.
  • Strong judgment about data quality, privacy, and the limits of what an analysis can support.
  • Comfort building standards and systems in an environment where the analytics function is still taking shape.
  • Practical experience with AI-assisted analysis and a disciplined approach to validating generated work.

Experience with B2B software, workflow products, customer implementations, or operational analytics is helpful but not required. We care most about analytical judgment, clear communication, and the ability to build something the team can trust.

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