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To apply, send your resume to careers@lgads.tv


We’re a leader in helping brands find unduplicated reach across a fragmented TV landscape, and maximize return on ad spend. We bring together years of experience in delivering premium home entertainment products to consumers worldwide, with big data and Video AI designed to connect brands with audiences across all screens.

Our platform brings together the two best TV industry leaders’ technologies and devices, to create one platform for activating and measuring media across connected TVs and digital video. Our actionable insights help marketers fine tune cross-screen campaigns in flight; and understand ad performance to optimize media buys.

Advertisers now have a single source for LG CTV inventory, with one-stop planning, activation and measurement across all viewing platforms. With our premium LG smart TV ad inventory, combined with deterministic TV data from a broad range of smart TV brands, LG Ads stands out for its expertise in reaching both massive-scale and granular custom audience segments, and for helping brands understand business outcomes from TV.

We are looking for data scientists / ML engineers who go above and beyond textbook solutions; critical thinkers who apply their expertise to solve unique problems and draw deep insights from this vast pool of data. You will have the opportunity to drive impact across the board, including making strategic decisions about our products and infrastructure.

Responsibilities:

  • Develop scalable data models, machine learning algorithms to facilitate data-driven decision making
  • Take advantage of massive amounts of structured data to understand end user behavior and help our advertising customers get better bang for the buck
  • Design and evaluate experiments
  • Use AI/deep learning techniques in conjunction with our ACR technology to extract deep insights
  • Be a thought leader and go-to expert on everything data

Requirements:

  • MS/PhD in Computer Science, Statistics, Engineering, or another relevant quantitative field
  • Experience with machine learning algorithms and/or statistical modeling
  • Proficiency in Python/R/Scala or other programming languages
  • Familiarity with Big data technologies like Hadoop, Map/Reduce, Spark, Hive etc. is a plus