Senior Data Scientist
Marketing
Confirmed live in the last 24 hours
Mercury

201-500 employees

Banking for startups
Company Overview
Mercury is on a mission to build a banking stack for startups. The company provides banking services and APIs for startups.
Fintech

Company Stage

Series B

Total Funding

$152M

Founded

2017

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

6%

2 year growth

102%
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
R
SQL
Segment
Google AdWords
Marketing
Google Analytics
CategoriesNew
Data & Analytics
Growth & Marketing
Requirements
  • 5+ years of experience working with marketing and advertising teams
  • Fluency in SQL and other statistical programming languages (e.g. Python, R, etc.)
  • Experience with non-technical marketing measurement tools such as Google Analytics, Amplitude, and various ad platforms like AdWords and Meta
  • Familiarity with tools like Segment and the technical aspects of sending measurement signals to ad platforms
  • Experience crafting data pipelines and dashboards, and understanding different database structures
  • Super organized and communicative, with the ability to prioritize and manage projects to maximize impact
Responsibilities
  • Collaborate with Marketing stakeholders and other cross-functional partners to identify impactful business questions, conduct deep-dive analysis, and communicate findings and actionable recommendations
  • Collaborate with other Data Scientists and Data Engineers to build and improve different marketing measurement capabilities
  • Collaborate with the Finance team on LTV and ROI calculations
  • Develop and apply marketing measurement capabilities such as A/B Testing, Marketing Mix Modeling (MMM), and Multi-touch Attribution (MTA) to evaluate the performance of our marketing effort
  • Build and deploy machine learning and statistical models such as Customer Lifetime Value, Lead Scoring, Segmentation, and time-series forecasting end to end
  • Influence and partner with engineering, design, and business teams to implement data-based recommendations