Senior Data Scientist, Marketing

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Full Remote
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Offer summary

Qualifications:

Bachelor's degree or higher in a quantitative discipline such as Statistics, Applied Mathematics, Economics, Computer Science, or Engineering., 8-10+ years of experience in analytics driving business decisions, particularly in marketing or product analytics., Strong technical skills in SQL and experience with large unstructured datasets, as well as proficiency in programming languages like Python or R., Deep understanding of statistical analysis, experimentation design, and analytical techniques like regression and decision trees..

Key responsibilities:

  • Evaluate and enhance marketing measurement techniques including Marketing Mix Modeling and Multi-Touch Attribution.
  • Conduct analytical deep-dives to identify hypotheses and design experiments for user engagement insights.
  • Create personalized segmentation strategies using propensity models for targeted marketing offers.
  • Build automated reporting and dashboards to track acquisition, monetization, and engagement trends.

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Dropbox Large http://www.dropbox.com
1001 - 5000 Employees
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Job description

Role Description

We're looking for a Senior/Staff Data Scientist to partner with Marketing, Brand, Product and Finance teams to answer key questions about the effectiveness of marketing across all our paid and owned channels. 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 marketing measurement methods (eg. causal inference, attribution, MMM) and strong technical fluency in scripting(Python/R) and querying(SQL)

Responsibilities
  • Evaluate and improve our marketing measurement leveraging techniques such as MMM(Marketing Mix Modeling), MTA(Multi touch attribution) and incrementality testing
  • Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
  • Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
  • 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.
  • Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
  • 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
  • Understand what matters most and prioritize ruthlessly
  • 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
  • 8-10+ 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 and large unstructured datasets such as Hadoop
  • Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
  • Solid background in running multivariate experiments to optimize a product or revenue flow
  • Strong verbal and written communication skills
  • Proficiency in programming/scripting and knowledge of statistical packages like R or Python
Preferred Qualifications
  • Experience in using open source packages for incrementality tests(e.g. Meta’s Geolift, Google’s Causal Impact) and MMM (Google’s Meridian, Lightweight MMM or Meta’s Robyn)
  • Master's or Ph.D. Degree in a quantitative field
  • Experience with predictive modeling, machine learning, and experimentation/causal inference methods.
Compensation
Canada Pay Range
$157,300$212,700 CAD

Required profile

Experience

Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Communication
  • Teamwork
  • Problem Solving

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