Director, Data Science

Posted 2 Days Ago
Be an Early Applicant
4 Locations
250K-441K Annually
Senior level
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
We believe the camera presents the greatest opportunity to improve the way people live and communicate.
The Role
The Director of Data Science will lead a team responsible for developing advanced data science methods to enhance ad performance and revenue growth. Responsibilities include managing machine learning models, delivering actionable insights through data analysis, and building relationships with executives. This role emphasizes strategic improvements using data and effective team leadership.
Summary Generated by Built In

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles.

 

The Director will be the go-to analytic partner for senior executives across sales, engineering and product and will lead the data science team responsible for DS support of revenue growth. The team is responsible for developing advanced data science methods to aid in ad performance understanding and investigations, return on investment measurement, and a deeper understanding of audience exposure, conversion and related activities impact.

This person will focus on driving business outcomes through strategic and operational improvements using data and delivering insights to advance our understanding of customer engagement and ad performance across our products. They will create and lead analysis on multivariate tests and drive a wide variety of cross-functional, high impact data projects and initiatives. He/she will lead an experienced team of data scientists aimed at increasing business results through the combination of statistical rigor, technical capabilities, strategic data analysis, and fast paced execution. 

Responsibilities:

  • Answer complex business questions by using appropriate statistical techniques.

  • Build and manage machine learning models aimed at providing better signals for ranking, modeling short and long term audience forecasts across varying scenarios as well as predicting user behavior.

  • Partner across the organization. Develop and maintain relationships with senior executives in the business lines and Engineering, ensuring their priorities are addressed.  

  • Maximize analytics value by improving data management, data quality and governance.

  • Build a high-performance team of data scientists and analysts.

  • Deliver insightful analysis and recommendations that can be acted upon by the organization at all levels.

  • Clearly articulate the approach and the findings of interpretable analytical models and drive the continuous refinement of what should be tracking and reporting.

  • Build out in-depth knowledge of the business success drivers (including determining the KPIs that will help meet our forecasts) and deliver value added solutions that have a measurable impact on the business.

  • Be hands-on and work with massive datasets with superior analytics skills. 

  • Drive pragmatic approaches to solving key complex business problems through data analysis, predictive modeling and machine learning techniques.

  • Manage multiple teams on different projects, ensuring timeliness and successful completion

  • Aid in integrating data science learnings/models with the technology tools to make insights actionable and results real-time.

Qualifications:

  • Consultative nature, with a proven track record of using data to achieve actionable results

  • Demonstrated experience in hiring, retaining, growing, and scaling diverse, geographically dispersed, high-performing DS and DE teams.

  • Proven experience influencing strategy and driving change with senior executives across org boundaries through clear and compelling communication of data-driven insights and analyses.

  • Experience in ML modeling, forecasting, data management, data quality and data/analytical governance tools and frameworks

  • 10+ years of work experience managing Data Science teams, working collaboratively with Product and Business teams, and guiding data-influenced product and business planning, prioritization, strategy, and execution.

  • Advanced degree in Mathematics, Statistics, Engineering, Computer Science, or a quantitative discipline, Ph.D. preferred.

 

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.

"Default Together" Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week. 

At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.

Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!

Compensation

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

Zone A (CA, WA, NYC):

The base salary range for this position is $294,000-$441,000 annually.


 

Zone B:

The base salary range for this position is $279,000-$419,000 annually.

Zone C:

The base salary range for this position is $250,000-$375,000 annually.

This position is eligible for equity in the form of RSUs.

Top Skills

Data Science
Machine Learning

What the Team is Saying

Xiaolin
Yvette
Matt
Jasmeet
Xueyin (Sherry)
Amir
Jung
Xu
The Company
HQ: Santa Monica, CA
5,000 Employees
Hybrid Workplace
Year Founded: 2011

What We Do

Snap Inc. is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. We contribute to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

Why Work With Us

Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

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Snap Inc. Teams

Team
Product + Tech
Team
Machine Learning @ Snap
About our Teams

Snap Inc. Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Our “default together” approach is an 80/20 model where we are asking team members to spend 80% of the time, on average, in the office, with the remaining 20% of the time spent remote.

Typical time on-site: 4 days a week
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