Data Science Manager

Location: San Francisco
Job Type: Analytics

IQ Workforce provides talent services for the analytics and data science communities.

Our client is one of the most successful technology startups in the last 10 years. They have grown to 300+ employees and service 15,000 stores across 4,000 cities. They just closed a $600 million round of funding, bringing their valuation to $7.6 billion (Oct 2018).

This client has a fast growing 20+person centralized data science team, made up of Managers and Sr. Data Scientists.  They are currently looking to add another experienced Manager to oversee a mid-size team (3-8+).

In this role you will lead a team of data scientists and be responsible for leveraging data to help your stakeholders learn and make better decisions. Your stakeholders include their product teams as well as their operations and your team will be driven by having a large impact on the success of these teams. You will strategically collaborate with senior product and operations leadership to achieve this.

Responsibilities include:

Attract, retain and develop world class data scientists

Have a high impact on your stakeholder teams, product and operations, and hold yourself accountable to measurable improvements in business outcomes

Design and analyze experiments, inclusive of but not limited to a/b tests

Define your stakeholders key metrics, and identify opportunities to improve those metrics through rigorous analysis

Empower your stakeholders to use data through self-service reporting and automated insights like anomaly detection

Be responsible for the health of your teams’ data – its completeness and its quality


2+ years of experience managing a team of data scientists with demonstrable success

Passion for, and a track record of leveraging data for business impact, preferably in a consumer facing digital environment

Ability to write complex and performant queries in your dialect of SQL to extract data from our data warehouse

Experience building tools and automated processes to extract, clean, and distill data in a procedural language of your choice such as Python, Julia or R

Understanding of A/B testing and other forms of statistical analysis using statistical packages similar to R, SAS, or Pandas


Advanced degree in statistics or other quantitative field

Data modeling, ETL and data pipeline development experience

Contributions to the technical community (e.g. open source, blogging, etc.)