Data Science Manager

Remote - US; Remote - Canada

Full Time Senior-level / Expert USD 94K - 190K *
Dropbox logo

Dropbox

Dropbox helps you simplify your workflow. So you can spend more time in your flow.

View all employer listings

Apply now Apply later

Role Description  The Data Science team is a central function that seeks to leverage data to help make better business decisions. This team leverages various data sources and quantitative techniques to synthesize narratives around how our customers use our products and develop critical insights and actionable recommendations for our business.   We are looking for a talented manager to lead a team of data scientists to answer critical questions about growing our revenue, transforming our business, and understanding the impact of our initiatives. In addition, you will collaborate with cross-functional leaders to develop a deeper understanding of our users to build the right product to meet their needs and achieve business objectives.   You will prioritize and align key analytics projects for your team and communicate quantitative insights and narratives broadly across all levels of the organization. You will also have the unique opportunity to define what data science means at Dropbox, influencing teams across the company to understand better how they can leverage information and insights to achieve their ambitious goals. Moreover, you will get the opportunity to lead a fantastic team of talented, curious, passionate data scientists to shape the future of our business.    Responsibilities
  • Build and manage a high performing team of data scientists
  • Coach and mentor data scientists of varying experiences to ensure their continued growth 
  • Plan, execute, and complete mission-critical data science projects and provide technical leadership in a fast-paced environment
  • Provide quantitative insights and perform analytical deep-dives to proactively identify growth opportunities and inform future learning, product experimentations, and product roadmaps  
  • Steer the team in creating ML models to optimize our payments processing or fraud detection
  • Identify key metrics and create automated dashboards to monitor and report on the health of the business
  • Simplify complex concepts to a broad audience, leaning on excellent communication skills, both verbal and written
  • Collaborate with cross-functional teams, including Product, Engineering, Design, Marketing, and Research, to execute against our roadmap quickly and iteratively
  • Understand what matters most and prioritize ruthlessly
Requirements
  • Bachelor’s degree in Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
  • 5+ years of industry experience as a data scientist
  • 2+ years of experience directly managing data scientists, quantitative researchers, or product analysts
  • Ability to lead a high-performing team and inspire others 
  • Ability to influence prioritization and execution of high visibility projects that affect customer experience as well as monetization
  • Experience analyzing large datasets and using data to inform product and business decisions that led to measurable outcomes
  • Exceptional verbal and written communication skills
  • Comfortable with SQL and large datasets, strong understanding of statistics, experimentation, and modeling

* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net

Tags: Computer Science Economics Engineering Machine Learning Mathematics ML models Research SQL Statistics

Perks/benefits: Career development Startup environment

Regions: Remote/Anywhere North America
Countries: Canada United States
Job stats:  8  2  0
Category: Leadership Jobs
  • Share this job via
  • or

Other jobs like this

Explore more AI/ML/Data Science career opportunities

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.