Sr. Product Analyst / Sr. Data Scientist

| United States | Remote
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By clicking Apply Now you agree to share your profile information with the hiring company. is the leading go-to-market solution for revenue teams, trusted by over 500,000 companies and millions of users globally, from rapidly growing startups to some of the world's largest enterprises. provides sales and marketing teams with easy access to verified contact data for over 270 million B2B contacts, along with tools to engage and convert these contacts in one unified platform. By helping revenue professionals find the most accurate contact information and automating the outreach process, turns prospects into customers. Apollo raised a series D in 2023 and is backed by top-tier investors, including Sequoia Capital, Bain Capital Ventures, and more, and counts the former President and COO of Hubspot, JD Sherman, among its board members. is growing rapidly, with 900% revenue growth since 2021, and is looking for world-class talent to keep building with us.

As the Sr. Product Analyst / Data Scientist supporting our Product & Growth verticals, you will be responsible for improving data-driven decision speed and quality, inherently helping shape Apollo’s overall strategy and product roadmap in the process. This role will be mission critical in standardizing how we scale and implement statistical analysis (e.g. hypothesis testing, regression analysis, causal inference), A/B testing, and other key measurement techniques across the firm that act as the qualitative lynchpin to our decision-making.

As Apollo continues to scale, data-driven decision making and predictive insights will be a critical asset to the company and thus, this role will have high visibility, agency, and autonomy to expand qualitative analysis at enterprise scale.  You and your peer group of product analysts will work closely with various product teams, data platform, business intelligence and product engineering teams, fostering collaboration, innovation, and continuous improvement. This role requires a strong blend of technical expertise, strategic thinking, and communication skills to guide our products' evolution and deliver maximum value to our customers. You will be reporting to the Sr. Manager of Product Analytics / Data Science, embedded within the broader Business Intelligence team that sits in the Revenue Operations organization.


  • 1. Partner with the Sr. Manager of Product Analytics / Data Science to drive the curation and execution of the Product Analytics & Data Science roadmap, partnering with our product leadership team to directly tie and correlate business strategy (OKRs and initiatives) into adjacent key predictive models, rich analyses, experiments, and department-specific reports/dashboards that aid in the measurement and execution of the key.
  • Provide tactical support for various data needs such as experiment setup, impact sizing, deep dive data exploration, and the development of critical self-service funnel or behavioral dashboards for product managers and squad engineering leaders to consume to help the real-time efficacy of key programs and features being launched to customers
  • Partner alongside data platform and business intelligence to map out the end-to-end flow of our product funnels with relevant events to be instrumented, metrics to be calculated, etc., manifesting in highly-governed tracking events, certified golden tables, and cross-functional data work streams that becomes the key infrastructure under the hood of statistical and predictive models
  • Partner alongside our machine learning team directly to help build various models in the context of personalization (i.e. auto-suggestions in search filters, highly targeted and contextually relevant feedback and recommendations gleaned from conversation/transcripts), forecasting (i.e. scoring and predictive insights on particular account and contact profiles best suited for engagement), and other key AI/ML-driven levers (i.e. improved sentiment analysis in sequences) that help improve our core product offering

About you:

  • Degree in Analytics, Applied Mathematics, Economics, Statistics or related analytical field of study or equivalent combination of training and experience
  • Deep and rich experience in working with critical exploratory analysis projects related to cohorting, time series analysis, funnel analysis/optimization is required
  • Expert-level proficiency with regard to influencing product strategy with SQL, A/B testing, machine learning, statistical analysis and/or related capabilities like R, Python, SAS, etc. is required
  • Current or former role(s) supporting SaaS (Product Led Growth) companies with qualitatively unraveling gaps and influencing recalibrated activation metrics (i.e. aha/habit moments) is a huge plus
  • Experience with Product Analytics tooling to track end-to-end journeys/funnels (i.e. Amplitude, Heap, Mixpanel, etc.) and analyzing events within those products is a must-have
  • In-depth experience with Business Intelligence tools (i.e. Looker) is a major plus


What You’ll Love About Apollo

Besides the great compensation package and culture that thrives in openness and excellence, we invest tremendous effort into developing our remote employees’ careers. The team embraces that we have a sole purpose: to help customers maximize their full revenue potential on the Apollo platform. This mindset opens us up to a lot of creative approaches to making customers successful at scale. You’ll be a significant part of a lean, remote team, empowered to really own your role as a proactive educator. We’re very collaborative at Apollo, so you’ll be able to lean on your teammates, even in adjacent departments, to help you achieve lofty goals. You’ll be supported and encouraged to experiment and take educated risks that lead to big wins. And, you’ll have a whole team remotely by your side to help you do it!

More Information on operates in the Sales industry. The company is located in San Francisco, California . was founded in 2015. It has 190 total employees. To see all 46 open jobs at, click here.
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