Open Opportunity

VP Data Science

Los Angeles

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Seeking a Head of Data Science & Analytics for profitable big data adtech startup in El Segundo.


Centerfield develops digital AdTech focused on real time biddable (RTB) media. Its platform delivers (at scale) high performing, high lifetime value customers to its clients across numerous industries and a variety of digital platforms, including search, display, video & mobile.

Centerfield leverages a proprietary and purpose-built end-to-end tech platform leveraging Big Data and optimizes each part of the customer acquisition process from initial view through offline sales in real time for the highest possible return on adv. spend.

This is a phenomenal oppty for a Data Science pro looking to:

  • Contribute and lead a team working w/ extremely large data sets
  • Be a key participant in new product & platform development from a technology leader
  • Take on the challenge of delivering actionable insights to clients and partners

Highlights include:

  • Founders have had multiple exits; invested/ran successful online companies such as Candy Club, VoiceStar (acquired by Marchex), HauteLook (Acquired by Nordstrom), AchieveCard (Acquired by Green Dot), Achieve Financial Services (acquired by Green Dot), Vendare Media and Interclick (acquired by Yahoo).
  • PROFITABLE and closing in on $100M in revenues while growing at > 40% annually
  • Top 10 of “Best Place to Work in LA” for the past 5+ years
  • Culture of social responsibility and giving back to the community while offering some of the BEST BENEFITS in the industry!
  • Developing leading edge technology in RTB, SEM, SEO etc. using Big Data on a variety of platforms


  • PhD in Statistics, Mathematics or related field
  • 4+ years of relevant experience working with data in the private sector
  • 4+ years of real world experience programming in R
  • Excellent SQL knowledge
  • Experience with a programming language such as C++, Java, Python or C# is huge plus
  • A strong ability in statistical modeling and analysis to provide rigorous solutions that address the business needs
  • Classification methods (e.g., Neural Net, Logistic Regression, Decision Trees, KNN, SVM, Random Forest)
  • Regression methods (e.g., Linear, Nonlinear, Boosted Regression Trees )
  • Clustering methods (e.g., K-means, Fuzzy C-means, Hierarchical Clustering, Mixture Modelling)
  • Time-series Modelling/Forecasting (e.g., AR, ARMA, GARCH, Exponential Smoothing)
  • Statistical Analysis (e.g., Hypothesis Testing, Experiment Design, Hierarchical Modeling, Bayesian Inference)
  • Strong problem solving skills, and an ability to apply them in the context of a fast-paced business environment
  • Good written and oral communication skills to translate complex models and analysis results into layman terms
  • Capable and motivated to collaboratively work with a diverse and innovative team of engineers, analysts, operations personnel and business management to deliver results.
  • Knowledge about Big Data related techniques (e.g., Map-Reduce, Hadoop, Hive, NoSQL)