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Senior Data Scientist - Product

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Location
United States
Apollo

Job Description

Apollo.io 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. Apollo.io 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, Apollo.io 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. Apollo.io is growing rapidly, with 900% revenue growth since 2021, and is looking for world-class talent to keep building with us.

Position Overview:

We are seeking a highly analytical and impact-driven Senior Data Scientist to help shape our product strategy and decision-making through data. In this role, you will focus on optimizing existing products while also supporting early-stage product initiatives where relevant. You will work closely with cross-functional teams to drive product innovation and optimization through data-driven insights. This position requires a passion for transforming data into actionable insights and the ability to thrive in a fast-paced environment.

What You’ll Do:

  • Translate business needs into data analysis and actionable insights to optimize product performance and user experience for both existing and new products.
  • Work closely with product managers, engineers, and other cross-functional stakeholders to identify critical product questions and provide data-driven solutions.
  • Develop and maintain a scalable, reliable, and accurate analytics infrastructure to support product decisions.
  • Establish and maintain best practices for data collection, analysis, and reporting.
  • Deliver actionable insights and recommendations focused on landing tangible product impact.
  • Help foster a culture of data-driven decision-making and continuous improvement within the product teams.
  • Ensure the integrity and accuracy of the data used for analysis and reporting.
  • While the primary focus is on existing products, support 0 to 1 product launches by identifying key metrics and analyzing early-stage product data when applicable.

What You Bring:

  • Strong experience in product analytics or a similar data-focused role, with a proven ability to impact product strategy and decision-making through data.
  • Expertise in translating complex data into insights that are actionable for cross-functional teams.
  • Proficiency with data analytics tools and platforms (e.g., Looker, Amplitude) is a plus but not required. A focus on solving product challenges is more important than specific tool experience.
  • Experience in building and maintaining reliable analytics infrastructures.
  • Excellent communication skills, with the ability to clearly present data insights to both technical and non-technical stakeholders.
  • Experience with 0 to 1 product initiatives is a plus, though not required.
  • A high level of accountability, a passion for continuous learning, and the ability to thrive in a fast-paced, dynamic environment.

Qualifications:

  • Degree in Analytics, Applied Mathematics, Economics, Statistics, or related analytical field of study, or an equivalent combination of training and experience.
  • Deep experience in working with exploratory analysis projects related to cohorting, time series analysis, and funnel analysis/optimization is required.
  • Expert-level proficiency in influencing product strategy with SQL, A/B testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc., is required.
  • Previous or current experience supporting SaaS (Product-Led Growth) companies with uncovering gaps and recalibrating activation metrics (e.g., aha/habit moments) is a huge plus.
  • Experience with Product Analytics tools to track end-to-end journeys/funnels (e.g., Amplitude, Heap, Mixpanel) and analyzing events within those products is essential.
  • Proven ability to thrive in a fast-paced, dynamic startup environment with a high level of adaptability and a strong product sense, ensuring insights align with customer needs and product goals.

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!

Advice from our career coach

A successful applicant for the Senior Data Scientist position at Apollo.io should have a strong background in product analytics and experience in influencing product strategy through data-driven insights. To stand out as an applicant, here are some specific tips and insights:

  • Demonstrate a proven ability to impact product strategy and decision-making through data analysis.
  • Show expertise in translating complex data into actionable insights for cross-functional teams.
  • Highlight experience in building and maintaining reliable analytics infrastructures.
  • Emphasize excellent communication skills in presenting data insights to both technical and non-technical stakeholders.
  • Showcase a high level of accountability, continuous learning mindset, and ability to thrive in a fast-paced environment.
  • Provide examples of previous experience with 0 to 1 product initiatives and using data analytics tools.
  • Highlight qualifications such as a degree in analytics, applied mathematics, economics, statistics, or related field and deep experience in exploratory data analysis projects.
  • Emphasize proficiency in influencing product strategy with SQL, A/B testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc.
  • Showcase experience in supporting SaaS companies with uncovering gaps and recalibrating activation metrics.
  • Illustrate a track record of thriving in a dynamic startup environment and aligning insights with customer needs and product goals.

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