WHO WE ARE

DoubleVerify is the leader in digital performance solutions, improving the impression quality and audience impact of digital advertising. Built on best practices, DoubleVerify solutions create value for media buyers and sellers by bringing transparency and accountability to the market, ensuring ad viewability, brand safety, fraud protection, accurate impression delivery and audience quality across campaigns to drive performance. Since 2008, DoubleVerify has helped hundreds of Fortune 500 companies gain the most value out of their media spend by delivering best in class solutions across the digital ecosystem that help build a better industry.

MINIMUM QUALIFICATIONS

• Bachelor’s degree in mathematics, statistics, engineering or related quantitative discipline, or equivalent experience
• 6+ years of full time working experience in quantitative analysis roles
• 3+ years of experience conducting business analyses and presenting insights/opportunities to upper management to inform key business decisions of senior leaders
• Strong analytical skills and critical thinking
• Proven experience in AdTech or a demonstrated knowledge of programmatic advertising, and the digital advertising ecosystem
• Advanced SQL proficiency and working in big data environments like Snowflake, Vertica, BigQuery, and Databricks/Spark
• Advanced experience in automated reporting using data visualization software: Tableau, Power BI, Looker, etc.
• Ability to work collaboratively in a fast-paced environment
• Excellent verbal and written communication skills
• Organized with a rigorous attention to detail

PREFERRED QUALIFICATIONS

• MBA or Master’s degrees in computer science, engineering, statistics, mathematics or related field
• Experience with at least one scripting language (Python, Java, C++, etc.)
  The successful candidate’s starting salary will be determined based on a number of non-discriminating factors, including qualifications for the role, level, skills, experience, location, and balancing internal equity relative to peers at DV.
  The estimated salary range for this role based on the qualifications set forth in the job description is between [$137,000 - $213,000]. This role will also be eligible for bonus/commission (as applicable), equity, and benefits.
  The range above is for the expectations as laid out in the job description; however, we are often open to a wide variety of profiles, and recognize that the person we hire may be more or less experienced than this job description as posted.

Not-so-fun fact: Research shows that while men apply to jobs when they meet an average of 60% of job criteria, women and other marginalized groups tend to only apply when they check every box. So if you think you have what it takes but you’re not sure that you check every box, apply anyway!

• This is a Hybrid position

ABOUT THE ROLE

We are seeking a bright, experienced Principal Product Analyst to support our Classification and Brand Safety product organization. The ideal candidate will excel strategically and be hands-on, executing big data analyses, demonstrating strong attention to detail, communicating effectively, possessing business acumen, and having keen product intuition.

WHAT YOU’LL DO

DoubleVerify is seeking a strategic, analytical, and innovative Principal Product Analyst to lead high-visibility analytics initiatives for our Classification and Brand Safety team. You will collaborate with product managers, engineers, and analysts to build comprehensive analytics and insights that drive our product feature roadmap and enhance our classification models. This role is integral to DoubleVerify, serving as a strategic thought partner to both product management and engineering teams, ensuring data-driven decision-making. Additionally, you will lead metrics reviews with partner teams and maintain a continuous feedback loop, highlighting key product KPIs and their impact on our roadmap.

KEY RESPONSIBILITIES

• Gather and analyze large amounts of information to discover & develop compelling, insightful recommendations.
• Evaluate and define success metrics with dashboards to guide decisions
• Conduct impact analysis of proposed product changes, evaluating feature alternatives, and designing experiments.
• Monitor key product metrics & system health, understanding the root cause of changes in metrics.
• Understand how the system works to determine how to best solve everyday issues as well as suggest new features that can solve ongoing ones.
• Influence product and engineering teams through the presentation of data-based recommendations.