Data Scientist II (Remote)

Department: Engineering
Location: US - New York
Updated on: July 18, 2022

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This job can be performed remotely from anywhere in the US


MediaMath’s strength is in numbers.  Our technology analyzes 200 billion customer opportunities daily– more volume than the top 10 stock exchanges in the world, combined. Over 700 Mathletes in 16 global offices are trusted by two-thirds of the Fortune 500 and partner with thousands of marketers to ensure brands connect with right audiences, in the right place, in the right time.

We believe consumers want to have meaningful conversations with their favorite and yet-to-be-discovered brands across all digital touchpoints. Our omnichannel, integrated programmatic platform unites digital media and big data to maximize the return on every marketing dollar spent by making advertising relevant, personalized, measurable and controllable.   

From inventing the DSP category in 2007 to being named a DMP Forrester Challenger (our first year participating in the DMP Wave!) in 2017, we continue to deliver results for marketers more quickly and accurately than any other solution. 

Technology is changing the way brands interact with consumers.  MediaMath is powering that change.  Come be a part of it!

We are currently looking for a Data Scientist II to support the ongoing development of MediaMath’s proprietary algorithms and analytics. This individual will be a member of the Data Science team, working closely with the Product & Engineering teams on the conception, design, development, testing, and deployment of real-world applications of models & data that impact billions of dollars of marketing spend. From optimizing real-time bidding auctions, to separating human from non-human web traffic, to building out a global cross-device graph across billions of users, this individual will have the opportunity to work on numerous cutting-edge problems and develop scalable, high-performance solutions to big data problems using state-of-the art technologies, languages and frameworks.

What you’ll do:

Design and develop Machine Learning models and algorithms that drive performance and provide insights, from prototyping to production deployment, across key areas of interest to the company (e.g., bidding optimization, messaging optimization, multi-touch attribution, fraud detection, device identification, cross-device association)


Partner closely with Engineering on the architecture and implementation of modeling efforts to ensure performance and scalability

Develop tools and processes to monitor performance of existing models and implement enhancements to improve scalability, reliability, and performance.

What you’ll need:


  • BS, Masters, or PhD degree in a quantitative discipline (e.g., Computer Science, Math, Physics, Statistics, Electrical Engineering, or similar)
  • At least 2-3 years of software development experience in Scala and/or Python.


  • Strong communication skills, and the ability to effectively discuss models with other data-scientists as well as business partners at the appropriate level of technical detail.
  • Strong quantitative skills, with solid grasp of key concepts in Probability, Statistics, Algorithm design, and Machine Learning.


  • Passion for hands-on "in-the-trenches" work with real-world data-sets..
  • Strong social skills and influence; outgoing personality type.
  • Fast learner
  • Analytic thinker
  • Creative problem solver

What's Next:  If there might be a match, you'll be scheduled for a first round interview; a 30-minute phone call with our recruiting team so we may get a better understanding of why you are interested in MediaMath and why you think it's a fit. We do our best to respond to everyone, however due to the volume of applications received, only those selected for interviews may be contacted.

What we offer: Company equity. Performance Bonus. Comprehensive Insurance. Global Internal Mobility. Open Paid Time Off, Philanthropy and Holidays. Perks galore. MediaMath is privately held, global company headquartered in @4WTC, New York City.