VP, Data Science

Department: Engineering
Location: Remote, US
Updated on: June 02, 2023

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About Us

MediaMath is the leading technology pioneer on a mission to make advertising better. We deliver outstanding results through powerful ad tech, partnership and a curiosity for what’s next. We help more than 3,500 advertisers solve complex marketing problems so they can deepen their customer relationships across screens and around the world.

We need talent like you to fuel this next-generation ecosystem.

US Proposed Salary Range: $231,000-$300,000 (Annual)

Key Responsibilities

MediaMath is seeking a leader of Data Science to help transform our engineering culture, to grow and develop our people, and to build the greatest tech possible.  The VP of Data Science designs and launches innovative and complex analytic models, utilizing a blend of contemporary and traditional data mining techniques, which, when applied to both structured and unstructured data sets, drive insights and benefits not otherwise apparent.  This person should have business domain expertise in order to translate goals into data-based deliverables, using quantitative analysis, statistical modeling, predictive and prescriptive analytics, optimization and attribution algorithms, pattern detection analysis, etc. This person should have knowledge of current AI and machine learning capabilities and should stay up to speed on advances in the field, both academic and applied. This person should be interested in the academics of data science, but more focused on practical application. This person should clearly articulate the purpose of data science solutions and then translate those into action. These solutions will encompass such things as product innovations and fixes, data architecture improvements, system architecture enhancements, business risks, and process improvements.

We are seeking an individual who thrives on describing a vision and then inspiring the team to achieve it.  A person who values giving credit over taking it.  We are looking for someone who will break down barriers, enlist and empower, communicate and stimulate.  Someone who harnesses advanced analytic data modeling systems to drive positive outcomes for our customers. From the definition of a strategy through the execution of it, you will develop, collect, and report the objective metrics required to assure it.  You will be responsible for driving employee engagement and productivity across Data Science and into Engineering

You will:

  • Define the vision for our data science applications, focused on up-leveling internal use of machine learning
  • Partner with our product teams to help predict system behavior, establish metrics, identifybugs and improve debugging skills
  • Ensure data quality and integrity within our products as well as our teams
  • Test performance of data-driven products
  • Partner with our client teams to enhance products and develop client solutions applyingcritical thinking skills to remove extraneous inputs
  • Conceive, plan and prioritize data projects
  • Interpret and analyze data problems
  • Lead data mining and collection procedures, especially focused on unstructured and siloed data sets
  • Build analytic systems and predictive models
  • Visualize data and create reports
  • Experiment with new models and techniques
  • Drive the implementation of models into Production through various Engineering teams
  • Manage, develop, coach, and mentor a team of Data Scientists, machine learning engineers and big data specialists
  • Create a positive culture to maximize productivity and minimize attrition

You are:

  • An innate personal interest in technology
  • Critical thinker
  • Strong attention to detail and extremely well-organized
  • Able to manage multiple projects with competing priorities
  • Able to understand business language
  • Able to work with diverse teams (product, engineering, analytics, sales, services) and atvarious levels within the organization
  • Demonstrate passion for excellence with respect to Engineering services, education, and support
  • Strong interpersonal skills, demonstrating an ability to work well with and enthusiastically influence teams & stakeholders

You have:

  • A strong focus on the client
  • Proven experience as a Data Scientist or similar role
  • Solid understanding of machine learning
  • Knowledge of data management and visualization techniques
  • A knack for statistical analysis and predictive modeling
  • Practical knowledge of machine learning tools and techniques. (e.g. Python Tensorflow,PyTorch, Spark, Scala)
  • Strong organizational and leadership skills
  • A business mindset
  • Excellent communication and analytics translation skills

Preferred Qualifications

  • Master’s or PhD in Statistics, Machine Learning, Mathematics, Computer Science,Economics, or any other related quantitative field. A working experience of the same is also acceptable for the position.
  • At least 7 years of working experience in a data science position, preferably working as a Senior Data Scientist.
  • Proven and successful track record of leading high-performing data analyst teams leading through the successful performance of advanced quantitative analyses and statistical modeling that positively impact business performance.

Why We Work at MediaMath

We are restless innovators, smart, passionate and kind. At the heart of our culture are three values that provide a framework for how we approach our work and the world: Win Together, Obsess Over Growth, and Do Good, Better. These values inform how we energize one another and engage with our clients. They get us amped to come to work.

Founded in 2007 as a pioneer in "programmatic" advertising, MediaMath is recognized as a Leader in the Gartner 2020 Magic Quadrant for Ad Tech and has won Best Account Support by a Technology Company for two years in a row in the AdExchanger Awards.

MediaMath is committed to equal employment opportunity. It is a fundamental principle at MediaMath not to discriminate against employees or applicants for employment on any legally-recognized basis including, but not limited to: age, race, creed, color, religion, national origin, sexual orientation, sex, disability, predisposing genetic characteristics, genetic information, military or veteran status, marital status, gender identity/transgender status, pregnancy, childbirth or related  medical condition, and other protected characteristic as established by law.