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Director of Data Science, Analytics

Director of Data Science, Analytics
NY, New York

Job Description

Management Responsibilities 

  • Meet with business stakeholders to flush out use cases and key requirements
  • Collaborate with data & technology teams to identify & source data sets required for analyses
  • Provide regular updates to and receive strategic direction from Global Data Science Team Lead 
  • Support Global Data Science Team Lead in setting up cadence of regular communication with senior level management and business stakeholders
  • Agree on project deliverable timelines with data scientists & relevant data, technology, and business partners; Manage project execution according to agreed timelines 
  • Provide direction to data scientists and review data science approaches, code, & deliverables
  • Prepare and communicate insights from analyses to Global Data Science Team, senior level management, and business stakeholders in clear business terms
  • Assist in making data science techniques approachable and understandable to non-data scientists
  • Identify appropriate data science solutions as new data-centric business problems arise 
  • Support Global Data Science Team Lead in developing and implementing data science framework, processes, and best practices
  • Stay current with new data science methods, technologies, and industry trends

 

Technical Responsibilities 

  • Apply data mining techniques to cleanse and explore large, complex data sets in preparation for further analysis
  • Apply appropriate data reduction, feature selection, and feature engineering techniques
  • Develop and implement hypothesis tests
  • Develop, validate, and operationalize appropriate mathematical and statistical algorithms and models; including implementation on large scale systems
  • Review, make enhancements to, and execute operationalized algorithms and models
  • Develop data products to communicate insights to business stakeholders
  • Collaborate with data & technology teams to create repeatable processes and scalable data products

Requirements

  • Master’s or PhD degree in a quantitative field (statistics, computer science, physics, etc.) 
  • Minimum of 5-8 years proven business experience and technical expertise in data science 
  • Experience cleansing and preparing large, complex datasets for analysis
  • Expertise applying statistics or machine learning in a professional or other intensive problem-solving environment with large, complex datasets 
  • Experience with hypothesis testing, clustering, regression & classification, time series analysis, & optimization
  • Expertise in statistical programming languages such as R or the Python scientific stack (NumPy, SciPy, scikit-learn, etc.)
  • Professional-level expertise in developing, validating, and executing algorithms and models on large scale systems
  • Experience with SQL
  • Experience with Amazon Web Services (RedShift, S3, EC2, EMR, etc.) and Apache Spark preferred
  • Familiarity with data visualization applications, like Tableau or RShiny
  • Self-starter with strong analytical, critical thinking, and problem solving skills
  • Excellent communication skills -- ability to present complex information in a concise and compelling manner
  • Previous management of data science project execution and data scientists 
  • Prior media or direct-to-consumer industry experience preferred

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