Senior Data Analyst, Customer Growth

We’re looking for a Senior Data Analyst, Customer Analytics to join MNTN’s Business Analytics team.

In this role, you’ll help drive how MNTN measures, understands, and improves customer outcomes across our connected TV advertising platform. You’ll work with advertising, campaign, account, product, and performance data to deliver insights, reporting, and analytical solutions that support better decision-making across the business.

This role partners closely with analytics, engineering, product, and business stakeholders to translate complex data into actionable recommendations and scalable customer analytics capabilities.

• Analyze customer behavior, campaign performance, product usage, account health, retention, and growth opportunities to identify actionable insights
• Design and maintain scalable data models and analytical datasets that support customer reporting, segmentation, forecasting, benchmarking, and executive reporting
• Build dashboards, recurring reports, and self-service analytics solutions that help stakeholders monitor performance and make informed decisions
• Translate ambiguous business questions into structured analyses, clear findings, and practical recommendations
• Apply analytical and statistical techniques, including segmentation, cohort analysis, forecasting, anomaly detection, and performance driver analysis, to solve customer-focused business problems
• Partner with cross-functional teams to define metrics, improve data quality, and ensure consistent reporting across the organization
• Validate analyses and reporting outputs through rigorous QA practices to maintain trust and accuracy
• Communicate insights, methodologies, and recommendations effectively to both technical and non-technical audiences

• You deliver accurate, high-quality customer analysis that helps teams understand performance, diagnose issues, and take action.
• You build trusted data models and reporting foundations that support customer analytics use cases at scale. Your work is well-documented, maintainable, and easy for teammates and stakeholders to understand.
• You independently drive ambiguous customer or business questions from initial request to clear recommendation. You clarify the problem, identify the right data, validate your findings, and communicate the answer in a way that is useful to both technical and non-technical audiences.
• You balance speed and rigor. You can move quickly when needed, but you maintain strong QA practices and a high bar for accuracy.
• You use advanced analytics pragmatically. You know when a simple SQL analysis is enough, when a cohort or segmentation analysis is useful, and when a lightweight predictive model or forecast can help the business make better decisions.
• You build trust with stakeholders by consistently delivering reliable data, clear explanations, and thoughtful recommendations.

• 5+ years of experience in data analytics, business analytics, customer analytics, product analytics, marketing analytics, business intelligence, or a related field.
• Strong SQL skills, with experience working in high-volume, large-scale data environments.
• Experience building scalable data models, analytical datasets, and reporting solutions that support repeatable analysis and decision-making.
• Proven experience analyzing customer behavior, campaign performance, product usage, retention, growth, or similar business outcomes.
• Proficiency with Python for analysis, automation, data transformation, validation, or lightweight modeling.
• Experience with Tableau or similar business intelligence and dashboarding platforms.
• Working knowledge of ETL/ELT processes, data pipelines, and data modeling best practices.
• Familiarity with statistical analysis, forecasting, segmentation, cohort analysis, experimentation, and predictive modeling techniques.
• Strong problem-solving skills with the ability to translate ambiguous business questions into structured analytical approaches.
• Excellent communication and stakeholder management skills, with the ability to explain complex analyses to technical and non-technical audiences.
• Experience managing competing priorities and delivering results in fast-paced environments.
• Experience in AdTech, MarTech, digital advertising, or media is a plus.