Staff Data Analyst - Product

Posted about 2 months agoViewed

💎 Seniority level: Staff, Extensive relevant experience

📍 Location: United States, Canada

💸 Salary: 130000.0 - 156000.0 USD per year

🏢 Company: Hootsuite👥 1001-5000💰 $50,000,000 Debt Financing almost 7 years ago🫂 Last layoff about 2 years agoDigital Marketing Social Media Marketing Social Media Management Apps

🗣️ Languages: English

⏳ Experience: Extensive relevant experience

🪄 Skills: PythonSQLBusiness IntelligenceData AnalysisData MiningMachine LearningMicrosoft Power BIProduct ManagementAmplitude AnalyticsProduct DevelopmentProduct AnalyticsAlgorithmsRegression testingCommunication SkillsAnalytical SkillsMentoringReportingJSONData visualizationData modelingA/B testing

Requirements:

Experience within a fast-paced business environment, with specialized experience in product data and analytics.
Ability to apply advanced statistical analysis, regression models, and predictive analytics to product data.
Strong ability to use visualization tools to translate complex product data into clear, actionable insights.
Experience analyzing user data to understand how customers engage with the product, identifying pain points and areas for improvement.
Ability to create customer segments based on product usage data and use insights to develop personalized product experiences.
Deep knowledge of how to track, evaluate, and optimize product performance based on key product metrics such as engagement, retention, and feature usage.
Expertise in writing complex SQL queries to extract and manipulate marketing data from relational databases.
Proficiency in Python or R for statistical analysis, data manipulation, and automation of reporting.
Experience working with product analytics tools like Mixpanel, Amplitude, or Heap for tracking user interactions and product feature usage.

Responsibilities:

Manage key cross-functional product analytics projects, tracking feature adoption, user engagement, and product performance.
Analyze product KPIs such as user retention, activation rates, churn, and lifetime value.
Work with the product team to develop and refine models that measure the impact of product features on key outcomes, such as user retention, conversion, and revenue growth.
Leverage product usage data to segment users based on behavior, demographics, and product usage patterns.
Lead A/B testing and controlled experiments to assess the impact of new product features, UI changes, and other user experience improvements.
Utilize statistical models and machine learning algorithms to forecast product trends, user behaviour, and feature adoption.
Mentor Data Analysts within the team through hands-on coaching and training to elevate their skills and impact.

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