Product Analytics Specialist

Reposted 13 Days Ago
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Hiring Remotely in IN
Remote
Mid level
HR Tech • Information Technology • Software
The Role
The Product Analytics Specialist at HackerRank supports product managers by analyzing data to guide product development and marketing efforts. Responsibilities include identifying key metrics, supervising data instrumentation, exploring datasets for insights, and designing user journeys to enhance product activation and retention.
Summary Generated by Built In

At HackerRank, we are on a mission to change the world to value skills over pedigree. We are a high-performing, mission-driven team that truly, madly, deeply cares about what we do. We don’t see velocity and quality as tradeoffs - both matter. If you take pride in high-impact work and thrive in a driven team, HackerRank is where you belong.

About the Team:

The Biz Ops & Analytics team partners closely with Product, Marketing, and GTM teams, delivering insights that directly shape HackerRank’s roadmap and market positioning. This cross-functional team sits at the core of our data-driven strategy.

About the Role:

As a Product Analyst II, you will work directly with product managers and designers to identify opportunities, guide prioritization, and evaluate product impact. You’ll play a pivotal role in improving activation, retention, and monetization across our platform.

What you'll do:

  • Partner with Product Managers and Designers to define success metrics and analyze feature effectiveness.
  • Develop user journey insights to improve activation, engagement, and retention.
  • Support GTM and Product Marketing teams with data stories that build HackerRank’s industry authority.
  • Own and execute ad-hoc and recurring product analyses using SQL, Python, and visualization tools.
  • Ensure data instrumentation quality and collaborate with Engineering on new tracking.

You will thrive in this role if:

  • You’re confident navigating large, imperfect datasets to deliver business-relevant insights.
  • You can work with minimal guidance and co-develop solutions iteratively with PMs.
  • You understand the product deeply, from user personas to competitive context.
  • You know when directional answers suffice and when precision is critical.

What you bring:

  • 4–5 years in analytics, with 2+ in product analytics (preferably SaaS or platform products).
  • Strong SQL and Excel skills.
  • Intermediate Python (Pandas, Numpy) for data wrangling.
  • Experience with A/B testing, funnel and retention analysis.
  • Hands-on with data visualization tools (Looker preferred, or Tableau/PowerBI).
  • Understanding of data modelling and partnering on new data warehouse tables.
  • Bonus: Familiarity with Pendo, Fullstory, Mixpanel or Google Analytics.
  • Bonus: Experience supporting ML/DS teams with data.
  • Bonus: Degree in Business Analytics, Data Science, MIS, or related field.

Want to learn more about HackerRank? Check out HackerRank.com to explore our products, solutions and resources, and dive into our story and mission here.

HackerRank is a proud equal employment opportunity and affirmative action employer. We provide equal opportunity to everyone for employment based on individual performance and qualification. We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. 

Linkedin |X | Blog | Instagram | Life@HackerRank|

Notice to prospective HackerRank job applicants:

  • Our Recruiters use @hackerrank.com email addresses.
  • We never ask for payment or credit check information to apply, interview, or work here.
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The Company
HQ: Mountain View, CA
1,053 Employees
On-site Workplace
Year Founded: 2012

What We Do

HackerRank is a technology hiring platform that is the standard for assessing developer skills for over 2600 companies around the world. HackerRank helps companies hire skilled developers and innovate faster by enabling tech recruiters and hiring managers to objectively evaluate talent at every stage of the recruiting process.

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