Lead Data Scientist

Lead Data Scientist

At Zenreach

Date Posted:


Zenreach solves a major problem for brick-and-mortar businesses—the majority of advertising is online, yet over 80% of purchasing still happens offline . Our platform links the two by automatically tracking in-store visits, creating rich audience profiles, and improving marketing for brick-and-mortar businesses.

We are backed by some of the biggest names in Silicon Valley. If you’re interested in joining a team that is changing the way the world does business, this might be the place for you.



Zenreach seeks a smart, curious, technically savvy, and experienced candidates to join our cutting-edge data science team. We hire the best and brightest and give them the opportunity to work on industry-leading technologies.

The data sciences team at Zenreach build predictive models and algorithms that power all our products at scale, develop methodology and tools to precisely and effectively target audiences and measure in-store visits, and research in-house and public data sources for consumer behavior insights.

In this role, you'll be spearheading the company’s advanced predictive modeling and analytical innovation to bring the analytical capability to the next level. In addition, you'll be expected to play an important role in carrying out R&D efforts.


  • Apply your expertise in quantitative analysis, data mining, and data visualization to see beyond the numbers, understand how our users interact and engage with Zenreach products, and draw actionable insights
  • Partner closely with product, engineering and marketing teams to solve big data problems and identify trends and opportunities
  • Lead the definition of product and business success metrics, collaborate with working teams to ensure correct data tracking instrumentation for measurement
  • Help set up experiments, analyze and interpret results
  • Build innovative big data products including predictive models, improvement of the company’s current data science, analytics and modeling frameworks, methodology and processes to improve offline measurement, audience profile creation, insights and dashboards reporting resulting in successful business outcomes for the company
  • Effectively communicate insights and recommendations to stakeholders
  • Lead ongoing decisions concerning data collection, test/study design and data analyses


  • RedShift, SnowFlake
  • Python
  • SQL
  • Linux
  • Tableau


  • Bachelors or Master’s in computer science, Statistics, Math, Finance, or other quantitative fields
  • 2+ years of professional experience with quantitative analysis
  • Experience in querying and manipulating large data sets using SQL
  • Understanding of statistics (e.g., hypothesis testing, regressions)
  • Knowledge in experimentation methods and/or predictive modeling
  • Ability to translate complex data into actionable insights for a non-technical audience
  • Experience with AWS or other Cloud Service provider


  • Be Committed: Work hard, Own the problem, Learn
  • Create Trust: Do what you say, Create trust with our Clients and Colleagues
  • Be Bold: Experiment, Speak up, Hope is not a plan
  • Deliver High Performance: Prepare, Commit, (over) Deliver


  • Excellent and comprehensive health plans (medical (including HSA/FSA and free access to One Medical), dental, vision, 401K)
  • Flexible work program with the ability to work remotely, or in-office - your choice!
  • Friday’s off from July 4 - Labor Day
  • Laptop and other equipment fundamentals (monitor, keyboard, and mouse if you need it!)
  • Flexible Vacation Policy
  • Enhanced Paternity/Maternity Programs


Zenreach is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law.

*Zenreach is an E-Verify participant

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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