Senior Data Scientist
Dropbox · Remote - US: All locations
Skills in this posting
Extracted from the posting text by the instrument — the demand side, read literally.
The posting
Role Description
We're looking for a Senior Data Scientist to partner with product, engineering, and design teams to answer key questions and drive impact in the Core Experience and Artificial Intelligence (AI) area s .
This area focuses on improving key part of the core product through re-envisioning the home experience, cross platform experience, user onboarding, and building new functionality and launching high impact initiatives.
We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle, behavior analysis, and customer segmentation.
We’re looking for someone who can bring opinions and strong narrative framing to proactively influence the business.
Responsibilities
Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes
Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends.
Identify opportunities, advocate for new solutions and build momentum cross-functionally to move ideas forward that are grounded in data.
Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate
Requirements
Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
8 + years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
Significant experience with SQL
Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
Strong verbal and written communication skills
Strong leadership and influence skills
Preferred Qualifications
Product analytics experience in a SAAS company
Masters’ or above in a quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus
Durable Skills
AI fluency means using these tools to amplify human judgment, not replace it. We believe people with these skills will thrive as work and technology continue to evolve:
Awareness: U nderstand yourself and others .
Judgment: E valuat e information and mak e decisions in complex situations .
Adaptability: L earn, adjust, and stay effective through change .
Connection: C ommunicat e , collaborat e , and build trust .
To learn more about why these skills matter and what the data shows about thriving through change, read this blog post from our Chief People Officer, Melanie Rosenwasser.
Compensation
US Zone 1
$193,000 — $261,000 USD
US Zone 2
$173,700 — $234,900 USD
US Zone 3
Excerpt from the original listing. The full, current text lives at the source. Read and apply there →
The PivotHop read
- What a data scientist actually earnsmedian, seniority, by country
- Data Scientist career changes, measuredevery measured route out
- All open data scientist rolesthe full board
Where these skills also reach
Adjacent occupations measured from the same postings — readiness is what a data scientist’s profile already covers.
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