Senior Data Product Analyst

About the role

Muttdata seeks a Senior Data Product Analyst to join its Strategy and Operations function. This position serves as the central authority for quantifying value within the company's AI product suite. The successful candidate will translate complex findings into strategic guidance for Product Management and executive stakeholders. Decisions regarding prioritization, performance evaluation, and portfolio expansion rely heavily on this role. The position operates with high visibility across the remote-first organization.

The analyst acts as a bridge between experimentation, engineering output, and commercial goals. They ensure that every stage of the product lifecycle is informed by rigorous evidence. This includes pre-launch hypothesis testing, live performance monitoring, and post-launch scaling initiatives. Continuous professional development is essential to keep analytical methods relevant to emerging business challenges.

Location and Engagement

The role is based in Argentina. The engagement model is fully remote. Compensation is set at sixty thousand United States dollars per year.

What you'll do

You will architect and implement a cohesive framework for measuring product performance across the entire AI suite, establishing the foundational logic that determines how success is defined and evaluated. This involves designing intake systems for analysis requests before any investigative work begins, ensuring alignment with strategic objectives from the outset. You will construct and maintain a sophisticated suite of dashboards focused on monitoring model behavior in production, providing real-time visibility into user interactions and system stability metrics. These tools will serve as the primary interface for stakeholders to understand the health and impact of data products.

You will conduct deep dives into the results of controlled tests and experiments, rigorously investigating anomalies and longitudinal trends to explain unexpected outcomes and surface hidden insights. Synthesizing complex analytical findings into clear, compelling narratives that justify further resource allocation and strategic investment will be a core part of your daily work. Your analysis must directly inform which features receive additional funding, iteration, or are scaled down based on evidence. Collaboration with commercial teams is essential to ensure that product metrics are tightly aligned with overarching revenue targets and business health indicators.

You will advise product management groups on the specific evidence that should guide future iterations and roadmap decisions, acting as a subject matter expert on data-driven product strategy. Working closely with engineering partners, you will verify that data infrastructure and pipelines are robust enough to support new analytical queries and evolving measurement needs. Communicating results and insights to non-technical leaders and stakeholders is a critical daily task, requiring the translation of technical jargon into actionable business language. The overarching goal is to enable swift, confident decision-making at all levels of the organization through clarity of data.

You will own the end-to-end analytical lifecycle for key products, from initial hypothesis formulation and metric design through to insight generation and stakeholder communication. You will identify opportunities to improve existing measurement frameworks and propose new methodologies to capture the true value of product initiatives. You will leverage advanced SQL queries to extract, transform, and validate data from complex datasets, ensuring accuracy and reliability in your analyses. You will utilize Python scripting to perform sophisticated statistical analysis, build custom models, and automate repetitive data processing tasks where appropriate.

You will create and optimize views within Looker to build intuitive, self-service dashboards that allow stakeholders to explore data independently and efficiently. You will write queries in BigQuery to handle large-scale data processing and derive insights from massive datasets stored in the cloud. You will manage version control for analytical code and documentation using Git to ensure reproducibility and collaboration. You will communicate primarily through Slack and manage project tasks and timelines diligently within Jira to maintain transparency. You will utilize Google Workspace for documentation, spreadsheets, and presentations, and leverage Zoom for virtual meetings and stakeholder updates.

Requirements

You must bring a minimum of three years of professional data analysis experience specifically within commercial or for-profit environments, demonstrating a track record of delivering impact. A solid, foundational grasp of statistical principles is necessary for rigorously evaluating model efficacy and interpreting experimental results. Fluency in English is mandatory for both written and verbal communication to ensure seamless collaboration across a remote, global team. Handling confidential data with the utmost integrity and strictly adhering to privacy protocols is non-negotiable and a core requirement of the position.

The ability to juggle multiple analytical requests and priorities simultaneously while maintaining organized documentation and clear methodologies is required. The role demands a high degree of precision and reliability in a fast-moving, dynamic environment where deadlines are critical. You must be highly self-motivated and disciplined, capable of driving your own workflow and output without direct supervision in a remote setting.

Nice to have

Direct exposure to artificial intelligence products and use cases is viewed favorably and provides a significant advantage in understanding the specific challenges of the domain. Previous experience working with large language models or recommendation systems is considered a distinct professional advantage. Familiarity with MLOps practices, model monitoring concepts, and the operational lifecycle of machine learning deployments is beneficial. Understanding business cases for technology investments and the ability to assess return on investment is also valuable for strategic alignment.

Practical notes

The engagement is fully remote and based in Argentina. The position operates on a standard work schedule within the Argentine time zone. Travel is not required as part of this role. There are no visa sponsorship requirements for this position. There are no specific application deadlines mentioned; interested candidates should verify current openings on the official application page for the most current information.