Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Senior Data Scientist – Product
- Remote from
- USA
- Salary
- USD 140k–200k / yr
- Department
- Data Science & Analytics
- Employment
- Full Time
- Experience
- Senior
- Published
- Apply before
- 14 Dec 2026
- Listing views
- 39
- Application actions
- 2
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About this role.
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. Founded in 2015, the company is one of the fastest growing companies in SaaS, raising approximately $250 million to date and valued at $1.6 billion. Apollo.io provides sales and marketing teams with easy access to verified contact data for over 210 million B2B contacts and 35 million companies worldwide, 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.
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.
The listed Pay Range reflects the total cash compensation inclusive of annual base salary and annual bonus as applicable. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonus target and annual base salary for the role. This salary range may be inclusive of several career levels at Apollo and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role who are not located in the US may request the annual salary range for their location during the interview process.
Additional benefits for this role may include: equity; company bonus or sales commissions/bonuses; 401(k) plan; at least 10 paid holidays per year, flex PTO, and parental leave; employee assistance program and wellbeing benefits; global travel coverage; life/AD&D/STD/LTD insurance; FSA/HSA and medical, dental, and vision benefits.
Tier 1 Pay Range (San Francisco, New York City, Seattle)
$160,000—$200,000 USD
Tier 2 Pay Range (All other US Locations)
$140,000—$176,000 USD
We are AI Native
Apollo.io is an AI-native company built on a culture of continuous improvement. We’re on the front lines of driving productivity for our customers—and we expect the same mindset from our team. If you’re energized by finding smarter, faster ways to get things done using AI and automation, you’ll thrive here.
Why You’ll Love Working at Apollo
At Apollo, we’re driven by a shared mission: to help our customers unlock their full revenue potential. That’s why we take extreme ownership of our work, move with focus and urgency, and learn voraciously to stay ahead.
We invest deeply in your growth, ensuring you have the resources, support, and autonomy to own your role and make a real impact. Collaboration is at our core—we’re all for one, meaning you’ll have a team across departments ready to help you succeed. We encourage bold ideas and courageous action, giving you the freedom to experiment, take smart risks, and drive big wins.
If you’re looking for a place where your work matters, where you can push boundaries, and where your career can thrive—Apollo is the place for you.
Learn more here!
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Role DNA
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Core skills
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Sample interview questions
I would first define activation using a validated behavioral milestone and specify the target population. I would run an A/B test with primary activation, guardrail, and downstream retention metrics, verify experiment quality, estimate the treatment effect with confidence intervals, and segment results to understand who benefits.
I would validate event instrumentation and data freshness before analyzing the funnel by cohort, channel, device, account segment, and release period. I would identify the largest step-level change, form hypotheses from session behavior and product changes, then prioritize follow-up analyses or experiments based on expected impact and confidence.
I use clear event definitions, ownership, automated data-quality checks, lineage documentation, version-controlled transformations, and monitoring for volume or schema changes. I also reconcile critical metrics with source systems and establish a regular process for reviewing instrumentation with engineering and product stakeholders.
I start with the decision, expected business impact, and confidence level rather than the methodology. I use simple visuals, explain key assumptions and limitations in plain language, and recommend a concrete next action while keeping technical detail available for stakeholders who need it.
I would work with the product team to define the customer problem, target users, success criteria, and a minimal event taxonomy before launch. After release, I would monitor adoption, activation, engagement, qualitative feedback, and leading retention indicators, using rapid learning cycles to refine both the product and its measurement plan.
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