closed vacancyData Scientist (Remote) - Media Industry Experience

Blue Orange Digital
Posted 3 years ago $90k - 110k (US Dollars)

This is a remote USA-based position within +/- 2 hours of Eastern Standard Timezones(NYC). 

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Job Description

You will be joining a highly talented team of engineers and data scientists working on implementing production machine learning models in the media space. We are helping a large company optimize their production models and further improve accuracy by leveraging additional 3rd-party datasets. This role will require exploratory model testing, production system maintenance, and collaboration with technical SME to improve performance, accuracy, and methodology. 

Responsibilities

  • Build machine learning models to solve forecasting, budgeting, optimization, and ranking problems. 
  • Work collaboratively with stakeholders across product and engineering teams to solve problems and deliver creative solutions.
  • Deliver machine learning solutions all the way to production and optimize production implementations.
  • Data cleaning and analysis, feature engineering, model training, and optimization in Python and Spark. 

Qualifications

  • BA/BS/MA degree in Computer Science, Math, Statistics, or a related technical field, or equivalent practical experience.
  • 5+ years of professional experience in data science, doing exploratory data analysis, testing hypotheses, and building predictive models.
  • A strong background in advanced mathematics, statistics, data mining, and machine learning.
  • Advanced experience in Python, proficiency with SQL, and experience with distributed computing frameworks like Spark. 
  • Demonstrable experience in working on optimization problems. 
  • Experience in Amazon AWS tools - SageMaker, S3, EC2, EMR
  • Experience with Snowflake preferred. 
  • Experience in the Ad &Marketing Tech fields is a huge plus.
  • Applicants must have strong written and oral communication in English. 
  • Interacts with others using sound judgment, good humor, and consistent fairness in a fast-paced environment