Data Scientist, Analytics & Behavior Science - Databricks

Data Scientist, Analytics & Behavior Science

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.

Comcast PABS (Product Analytics and Behavior Science) team is and always will be a technical team. 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.

Responsibilities:
•   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 iteratively 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, and 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

Qualifications:
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 an 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
•   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

 

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