Data Science Team Manager

Scribd   •  

Toronto, ON

Industry: Media

  •  

8 - 10 years

Posted 96 days ago

This job is no longer available.

We value trying new things, craftsmanship, being an open book, and the people that make our team great. Join us and build something meaningful.
Our data science team is small but mighty, digesting terabytes of data, making sense of it, and delivering key insights that drive both business and product decisions. The team works on every aspect of the business so you’ll touch everything we do and have an impact on all aspects of Scribd.Reporting to the Head of Data Science, you will assume leadership of a team that currently includes two Data Scientists. We anticipate that this team will grow to as many as seven over the nextyear or so. Initially, the role will include individual contributor work, but that should diminish as the team expands.At present one Data Scientist focuses on machine learning and the other on payments and fraud. However, we are open to your suggestions for organizing the team and work moving forward. The team is involved in a lot of activities, including product science, A/B test design, exploratory analyses, modeling and more. You'll oversee the team, providing technicalsupport, managing performance, training/coaching, assigning work, monitoring progress, and more.The team is expected to:* Provide decisionsupport to the whole company by doing analysis, building predictive models, creatingreports - doing whatever it takes - tosupport data needs across the organization.* Becoming domain experts in all aspects of the Scribd business, product, and data model; use this expertise to provide advice to all teams in the usage of our data.* Solve ambiguous problems.* Collaborate with stakeholders to determine the highest-impact opportunities.You also will interact regularly with the Data Science team and others in our San Franciscolocation.

To be a good fit, you'll have:

    • A bachelor's degree or higher in math, stats, CS, or physics, or equivalent experience.
    • 8 to 10 years of progressive experience, including a couple of years at the management level.
    • Solid professional experience in data science, and familiarity with at one or more of the following; NLP, recommendation systems, neural networks, predictive modeling.
    • Experience writing in SQL.
    • Experience with a scriptinglanguage like Python, R, etc.
    • Knowledge of A/B testing.
    • Experience designing metrics such as success metrics.
    • Willingness to roll up your sleeves to achieve goals.
    • The ability to adapt as our company grows and evolves.