Head of Data Analytics

Head of Analytics or Director/VP of Analytics

• 55 Grace St, San Francisco, CA 94103, USA
• Full-time

Company Description

The League is a pre-series A mobile social dating app startup backed by IDG Ventures, x-Seed Capital, Cowboy Ventures, Structure Capital, Sherpa Ventures, and many notable angels. The Founder is a Stanford MBA (ex-Google, ex-Salesforce) with a strong product sense (engineering degree from Carnegie Mellon) and a fierce determination to change the dating space for the better. The League’s director of engineering, Tim Zaitsev, has a masters from Carnegie Mellon and is incredibly hands-on and is building out a lean team of world-class, senior engineers. The League is live in six cities, brings in healthy revenue each month, and has hundreds of thousands of people in other metros waiting for its launch in their cities.

Job Description

This candidate leads the analytics department and oversees the activities of the junior departments and personnel. In this role, the Head of Analytics ensures that the business in its various departments understands its health, finds growth levers, and identifies opportunities for optimization. The Head of Analytics leads the business through all efforts that drive business performance and potential by using the existent and new data sources and techniques. He/she leads the data analytics department in the development of a departmental culture, policies, and strategy. The role will involve the Head of Analytics getting his or her hands dirty and solving hard analytical problems for the business, taking a seat at the table alongside Engineering, Product, and Marketing, often representing both Analytics and Product Operations.

1) Build the team

Determine what roles are most needed for the business

Attract and source candidates

Select candidates who will be the best fit for the company's needs and culture

Close candidates, often against competitive offers

2) Manage the team

Ensure a bright, enthusiastic, and capable team is aligned to and deployed against projects with the highest business impact

Help analysts and business intelligence engineers achieve their career goals. Make sure that team members understand how to have an impact and make sure they are aware of that impact when they've made it. Explain complicated stats or data technology concepts.

3) Guide the work (and do some of it yourself as well!) across a wide area of responsibilities

Marketing

Paid acquisition optimization, including LTV predictions, attribution models

Television, radio, and another point in time attribution

Billboards and possibly other geo-lift attribution

Brand awareness/affinity metrics

Tracking across different products, properties, and platforms

Ops

Operational metrics for customer support (ticket times, agent productivity, etc.)

Operational metrics for queue/back office tasks

Understanding how service speed and quality affect business metrics

Product

Continuing to dig deeper into the drivers for performance

User segmentation