Digital Product Analyst

Digital Product Analyst

Requirements

• 3+ years of relevant work experience analyzing and optimizing website performance, user behavior, traffic patterns, and conversion metrics.
• Strong background in analytics, understanding of concepts like Statistical Significance.
• BA/BS in Mathematics, Statistics, Finance, Marketing, Economics, or a related field.
• Exceptionally high standards in communicating the results of analysis clearly and effectively.
• Strong verbal and written communication skills and confidence to deliver technical information succinctly and assertively to non-technical audiences.
• Complex problem-solving and critical thinking skills, along with a solutions-oriented mindset.
• Intermediate knowledge of Excel, including the ability to use formulas, functions, and pivot tables.

Responsibilities

• Strategize with the embedded team to develop a cohesive and comprehensive understanding of the key drivers of the business, and leverage that understanding to achieve goals and move the company forward.
• Ingest and aggregate key performance data, KPIs and operational data sets (for example keywords/groups, ads, bidding, creative assets, etc.) to build structured models and analysis to drive insights and actionable intelligence.
• Analyze and diagnose website performance, user behavior, traffic trends, and conversion metrics to identify patterns and provide actionable insights to drive growth, optimization, cost-cutting, and performance improvement.
• Conceptualize and utilize statistical methods and data visualization techniques to convey a compelling business case for implementing recommendations based on data insights. Begin to build relationships with the Data Science Team for advanced data modeling.
• Proactively share insights and strategic recommendations with measurable and sizable business impact, offering data-driven recommendations to optimize pages, improve user experience, and enhance conversion rates, aligning with the goals of multiple business units.
• Partner with the Yield and Data Science teams to drive decision-making via critical, time-sensitive insights about our publisher partners, ad placements, and opportunities to improve KPIs.
• Drive meaningful conversations with Data Engineering and Data Analytics to improve data access, data platform, data flow, and data accuracy.
• Pivot quickly and smoothly between high-priority projects and changing business needs based on goals.
• Foster solid working relationships with co-workers, leadership, and stakeholders to develop and maintain alignment in priorities, strategy, and vision across crucial initiatives.

Preferred Qualifications

No preferred qualifications provided.