Senior Data Analyst (L4)

Description

The Opportunity

We are looking for a proactive, growth-minded Senior Data Analyst / ML Engineer with a minimum of 5 years of experience in analyzing high-volume data and delivering strategic insights. This is a unique "growth-track" role: you will start by mastering our data landscape through advanced dashboarding and telemetry analysis, then rapidly transition into building and maintaining the predictive models that drive our customer success.

If you are someone who isn't just looking for a ticket to solve, but wants to understand the why behind the numbers to proactively prevent customer issues, you’ll fit right in.

The Roadmap

• Phase 1 (Domain Mastery & KPI Strategy): You’ll dive deep into our telemetry and customer profile data. You will define the Key Performance Indicators (KPIs) that matter most and build high-impact Tableau dashboards to track them
• Phase 2 (ML Innovation & Production): Once you’ve mastered the domain, you will lead the transition into predictive modeling. You will own the feature engineering process and deploy models that proactively solve customer issues

What You’ll Do

• Dashboarding & Domain Learning: Initially, you will focus on building interactive and insightful Tableau dashboards. This is your foundation to learn our domain knowledge, understand customer behavior, and identify patterns in our telemetry data
• Feature Engineering: Architect and transform raw telemetry and customer profile data into high-signal features. You will build the data pipelines that serve as the foundation for all ML initiatives
• ML Development & Lifecycle Management: Develop and deploy ML models (churn prediction, anomaly detection, etc.). You are responsible for maintaining models in production, including setting up automated retraining pipelines to ensure accuracy as data evolves
• Proactive Problem Solving: Use your technical expertise to identify potential customer friction points before they become issues, moving the company from a reactive to a proactive stance
• KPI Development & Stakeholder Presentation: Collaborate with leaders to define critical business KPIs. You will act as a data storyteller, presenting key insights to executive stakeholders and translating complex ML/Data trends into clear, strategic recommendations

Qualifications

What You Bring

• SQL Mastery: You write clean, efficient, and complex queries at an expert level. This is the core of how you interact with our data
• BI & Dashboarding Expertise: Proficiency in Tableau, creating interactive dashboards that drive action and help you (and the team) rapidly acquire domain knowledge
• GCP Ecosystem: Strong experience with Google Cloud Platform, specifically BigQuery and its integration with ML tools
• ML Ops Experience: Practical experience managing the production lifecycle, monitoring, versioning, and ensuring timely model retraining
• The "Proactive" Edge: A strong desire to learn the business domain and grow with the company. You don't wait for instructions; you identify opportunities and solve problems before they escalate
• Excellent Communication Skills: A proven track record of analyzing high-volume data and presenting key findings to senior-level audiences. You can explain complex technical concepts to non-technical stakeholders with ease

Preferred Qualifications (Good to Have)

• GCP Professional Machine Learning Engineer Certification
• Working knowledge of leveraging Claude in the workflows
• Experience with Google Vertex AI or Kubeflow for ML orchestration
• Background in analyzing high-volume telemetry or IoT data

Technical Stack

• Languages: SQL (Expert), Python
• Data Warehouse: Google BigQuery
• Cloud Infrastructure: Google Cloud Platform (GCP)
• Visualization: Tableau, Looker, Etc
• ML Tools: Scikit-learn, TensorFlow/PyTorch, Vertex AI (GCP) , Claude (Anthropic)