Apollo. io

SaaS

StaffDataScientistProduct

$205–295k United States FULL TIME Remote Friendly
The Brief

“Staff Data Scientist - Product at Apollo. io. Skills: Product analytics, Data science, Machine learning, Statistical analysis. Translate business needs into data analysis and actionable. Optimize product performance and user experience”

Industry & Context.

SaaS
Problems you'll solve

Problem solving

What They're Looking For.

Must Have

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, Expert-level proficiency in influencing product strategy with SQL, A testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc, Experience with Product Analytics tools to track end-to-end journeys/funnels (e.g., Amplitude, Heap, Mixpanel) and analyzing events within those products

Nice to Have

PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, Dbt Certified certification, Experience with Product Analytics tools (e.g., Looker, Amplitude), Experience with 0 to 1 product initiatives, Previous or current experience supporting SaaS (Product-Led Growth) companies with uncovering gaps and recalibrating activation metrics (e.g., aha/habit moments)

What You'll Do.

Translate business needs into data analysis and actionable

Optimize product performance and user experience

Support early-stage product initiatives

Work closely with product managers

Identify critical product questions

Provide data-driven solutions

Develop and maintain scalable

and accurate analytics

Support product decisions

Establish and maintain best practices for data collection

Deliver actionable insights and recommendations

Focus on landing tangible product impact

Foster a culture of data-driven decision-making

Foster a culture of continuous improvement

Ensure the integrity and accuracy of the data

Support 0 to 1 product launches

Analyze early-stage product data

How You'll Work.

Team & Collaboration

Cross-functional teams; Product managers; Engineers; Stakeholders

Communication Scope

Present data insights

Free ATS check

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