11 days old

Data Scientist

Philadelphia, PA 19103
  • Job Code

Data Scientist (Big Data)

As a Data Scientist, you will evaluate and improve Comcast's products. You will collaborate with a multi-disciplinary team of engineers, researches and business on a wide range of problems. This position will bring engineering, analytical rigor and statistical methods to the challenges of measuring quality, improving consumer products, and understanding the behavior of users.

We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on millions, of users. Data scientists not only revolutionize our products, they play the role as interpreter. We see data as the voice of our users at scale, and as interpreter, we explain to product managers, engineers, business, marketing how customers use Comcast products. This enables people and machines to be able to make data driven decisions. PABS team supports Mobile/Web/STB Video platforms, iOT platforms, Mobile Platforms, Ai Platforms, and hardware products as well as our internal data products.


  • Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Build and prototype analysis pipelines to provide insights at scale. Develop comprehensive understanding of Comcast data structures and metrics, advocating for changes where needed for both products development and business/sales activity.
  • Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for, design, and assess improvements to Comcast products.
  • Make product recommendations (e.g. cross-platform analysis, behavior analysis, feature analysis, engagement/churn, cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
  • Research and develop analysis, forecasting, and optimization methods to improve the quality of Comcast's user facing products

Minimum qualifications:

MS degree in a quantitative discipline (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering).

  • 3 years of relevant work experience in data analysis or related field. (e.g., as a engineer / data scientist / computational social scientist / Behavior Scientists / etc).
  • Strong foundation in product analytics, statistics and machine learning
  • Keen eye for detail and thoughtful investigation of data before relying upon it
  • Ability to think and execute at multiple altitudes: from strategy and vision to execution
  • MS in quantitative field preferred (CS, Physics, Data Science, or similar)
  • Strong Experience in data science in writing code in SQL & Python (Scala, Unix)
  • Strong Experience operating in Big Data Pipelines (Spark, Hive, Presto, SQL engines) batch and streaming
  • Strong Experience in data story telling with visualizations
  • Strong Experience in developing and deploying Machine Learning models (Scikit-learn, MXNet, TensorFlow, H20, MLib or similar)
  • Self Starter/Driven personality
  • Enjoys fast paces culture

Preferred qualifications:

  • PhD degree in a quantitative discipline as listed in Minimum Qualifications.
  • 3 years of relevant work experience e.g., as a engineer / data scientist / computational social scientist / Behavior Scientists / etc), including deep expertise and experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods. Analytical engagements outside class work while at school can be included.
  • Applied experience with machine learning on large datasets (Spark)
  • Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations.
  • Demonstrated skills in selecting the right statistical tools given a data analysis problem. Demonstrated effective written and verbal communication skills.
  • Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.


  • Information Technology

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