

Oak Tree Software
Product Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
Nothing Found.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 19, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#Looker #AI (Artificial Intelligence) #Amplitude #SQL (Structured Query Language) #Jira #A/B Testing #Datasets #Leadership #SaaS (Software as a Service)
Role description
Job Title: Product Analyst
Location: 100% Remote - US
Exp - 4+ years of product analytics experience in tech or SaaS companies
Shift/Hours: (M-F) 40 hours/week with an overlap of 6 hours with PST.
Role Overview:
• We’re looking for a Product Analyst who has worked closely with product teams and knows how to turn ambiguous questions into clear, decision-driving insights.
• This is not just about pulling data—it’s about understanding the “why” behind requests, framing the right analysis, and communicating findings in a way that influences product direction.
• In this role, you will help create and evaluate realistic analytics scenarios and artifacts for an AI benchmark.
• You’ll bring strong analytical thinking, practical experience with experimentation, and the ability to reflect how real-world product analytics actually works—messy data, evolving metrics, and all.
What does day-to-day life look like?
• You’ll operate as both an analyst and a builder of realistic product analytics environments:
• Translate product questions into structured analytical approaches and clearly defined problem statements
• Conduct analyses on product metrics such as activation, retention, and engagement
• Design, support, and evaluate A/B tests, including defining success metrics and interpreting results
• Write high-quality analytical artifacts—experiment summaries, deep-dive memos, stakeholder updates, and more
• Review analytics outputs (docs, Slack threads, Jira tickets) for realism and quality—does this reflect how real teams work?
• Push for clarity when requests are vague—understand what decision the analysis is meant to inform
• Navigate messy datasets, imperfect tracking, and inconsistent metric definitions while still producing useful insights
• Communicate findings effectively across formats—from quick Slack updates to detailed reports for leadership
Requirements:
Core Experience:
• 4+ years of product analytics experience in tech or SaaS companies
• Experience working directly with product managers and cross-functional teams
• Proven track record of writing analysis docs, experiment summaries, or stakeholder-facing insights
Analytical & Technical Skills:
• Strong SQL skills and hands-on experience with analytics tools (e.g., Amplitude, Mixpanel, Looker)
• Experience running or supporting A/B tests and analyzing experiment results
• Solid understanding of key product metrics, including activation, retention, and engagement
• Comfortable dealing with ambiguous or evolving metric definitions and helping teams align on measurement
Ways of Working:
• Ability to scope ambiguous requests and clarify the decision they are meant to inform
• Strong written communication skills across formats (Slack, email, detailed memos)
• Experience managing incoming analysis requests or mentoring junior analysts is a plus
• Comfortable working with imperfect data and making thoughtful, well-reasoned recommendations
Job Title: Product Analyst
Location: 100% Remote - US
Exp - 4+ years of product analytics experience in tech or SaaS companies
Shift/Hours: (M-F) 40 hours/week with an overlap of 6 hours with PST.
Role Overview:
• We’re looking for a Product Analyst who has worked closely with product teams and knows how to turn ambiguous questions into clear, decision-driving insights.
• This is not just about pulling data—it’s about understanding the “why” behind requests, framing the right analysis, and communicating findings in a way that influences product direction.
• In this role, you will help create and evaluate realistic analytics scenarios and artifacts for an AI benchmark.
• You’ll bring strong analytical thinking, practical experience with experimentation, and the ability to reflect how real-world product analytics actually works—messy data, evolving metrics, and all.
What does day-to-day life look like?
• You’ll operate as both an analyst and a builder of realistic product analytics environments:
• Translate product questions into structured analytical approaches and clearly defined problem statements
• Conduct analyses on product metrics such as activation, retention, and engagement
• Design, support, and evaluate A/B tests, including defining success metrics and interpreting results
• Write high-quality analytical artifacts—experiment summaries, deep-dive memos, stakeholder updates, and more
• Review analytics outputs (docs, Slack threads, Jira tickets) for realism and quality—does this reflect how real teams work?
• Push for clarity when requests are vague—understand what decision the analysis is meant to inform
• Navigate messy datasets, imperfect tracking, and inconsistent metric definitions while still producing useful insights
• Communicate findings effectively across formats—from quick Slack updates to detailed reports for leadership
Requirements:
Core Experience:
• 4+ years of product analytics experience in tech or SaaS companies
• Experience working directly with product managers and cross-functional teams
• Proven track record of writing analysis docs, experiment summaries, or stakeholder-facing insights
Analytical & Technical Skills:
• Strong SQL skills and hands-on experience with analytics tools (e.g., Amplitude, Mixpanel, Looker)
• Experience running or supporting A/B tests and analyzing experiment results
• Solid understanding of key product metrics, including activation, retention, and engagement
• Comfortable dealing with ambiguous or evolving metric definitions and helping teams align on measurement
Ways of Working:
• Ability to scope ambiguous requests and clarify the decision they are meant to inform
• Strong written communication skills across formats (Slack, email, detailed memos)
• Experience managing incoming analysis requests or mentoring junior analysts is a plus
• Comfortable working with imperfect data and making thoughtful, well-reasoned recommendations






