Applied Data Scientist, Monetization
Snap Inc. is a camera company. We believe that reinventing the camera represents our greatest opportunity to improve the way people live and communicate. Our products empower people to express themselves, live in the moment, learn about the world, and have fun together.
We’re looking for Applied Data Scientists to join our Monetization Engineering Team. We are looking for a candidate experienced in causal inference and/or machine learning, and who understands ad technology, auctions and ads marketplace. Working closely alongside engineering, product management, and business product partners, you will be central to creating inventive, data-based approaches to solve difficult business and product problems.
Applied Data Scientists at Snap design implementable and scalable solutions, and productionalize them. We sit at the cross section of data science and machine learning. We provide impactful, objective, and actionable data insights that enable informed engineering and product decisions. We drive informed and timely decision-making that improves and optimizes the way our products are created, executed, and adopted.
What you’ll do:
Partner with the Product and Engineering teams, and apply your expertise in quantitative analysis, data mining, and machine learning to create insights and predictions
Create and test hypotheses in a causal inference framework
Build models and machine learning pipelines to solve problems in the monetization space:
understand how users interact with ads on the platform
predict churn and retention of clients
work on identity solutions in a privacy-preserving way
measure incremental revenue from advertising campaigns with experimental and observational causal inference techniques
work on attribution models, media-mix-models, lifetime value models
Understand patterns in data to identify key product trends and new product opportunities
Knowledge, Skills & Abilities
Excellent verbal and written communication skills, with high attention to detail
Strong statistical knowledge
Ability to initiate and drive projects to completion with minimal guidance
Ability to communicate the results of analyses in a clear and effective manner to a senior audience
Excellent problem-solving skills, and the ability to structure ambiguous business challenges into actionable plans
Ability to write close-to-production code
Minimum Qualifications:
M.S. or PhD in CS, Math, Physics, Statistics, Econometrics, or other quantitative field
3+ years of experience in machine learning, experience with the entire lifecycle of an ML model, from POC to productionalization
3+ years of experience in causal inference techniques, experimental design and/or A/B testing
Fluency in SQL or other big data querying languages
Solid experience with programming languages such as Python or R
Preferred Qualifications:
Track record of building scalable solutions in production environments
Experience with modern deep learning frameworks such as tensorflow or pytorch
Familiarity with cloud computing stack in AWS or GCP
Prior experience with ad measurement or ad tech
Experience in one or more of the following: graph analysis, recommender systems, uplift modeling, encoders
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. If you have a disability or special need that requires accommodation, please don’t be shy and contact us at [email protected].