Data Analyst (Data Science)

Data Analyst (Data Science)
CT, Stamford

Job Description

Key Responsibilities:

  • Develop predictive and descriptive models using advanced statistical, optimization, and big data techniques including: multivariate, regression, decision trees/classification, and time series
  • Assist in identifying critical questions to be answered and contribute to developing analytics-driven solutions and KPIs to enable more effective decision making
  • Conduct analysis and data modeling to draw insights that drive critical decision making and to uncover subscriber patterns, user content consumption, and customer behavior patterns
  • Create models, KPIs, and dashboards to operationalize outcomes of analytics
  • Monitor effectiveness of analytical models and ensure accuracy of all data from source to final deliverable through a systematic data quality control process
  • Work in complex data environment comprising several heterogeneous internal and third party data sources, manipulate large data sets and navigate a variety of servers, data types, and data structures to complete statistical and other analyses
  • Work on self-serve delivery, automation, and maintenance of reports and visualizations
  • Work with IT partners (e.g., data warehousing team) to design optimal data architecture for analytics and BI tools


Qualifications:

  • At least 1 year of experience in marketing/sales analytics, segmentation, and forecasting
  • At least 1 year of experience with a statistical analysis tool like R, SAS or SPSS
  • At least 1 year of experience performing data management, mining, and manipulation
  • Proficiency in a wide range of analytical methods including multivariate, time series, classification, and machine learning  
  • Working knowledge of SQL and relational data model
  • Working knowledge of at least two technologies: Python, Big Query, Google Analytics, Spotfire, and/or Tableau
  • Ability to translate quantitative results into clear and concise business presentations/reports using compelling data visualization techniques
  • Able to write code to query and transform both unstructured and structured data
  • Proven track record of identifying and highlighting key insights, signals, and trends deep within the underlying data
  • Bachelor’s degree in Statistics/Mathematics,Econometrics/Economics, Engineering/Computer Science, Business/Finance, or related quantitative field
  • Advanced degree a plus

 Key Responsibilities:

  • Develop predictive and descriptive models using advanced statistical, optimization, and big data techniques including: multivariate, regression, decision trees/classification, and time series
  • Assist in identifying critical questions to be answered and contribute to developing analytics-driven solutions and KPIs to enable more effective decision making
  • Conduct analysis and data modeling to draw insights that drive critical decision making and to uncover subscriber patterns, user content consumption, and customer behavior patterns
  • Create models, KPIs, and dashboards to operationalize outcomes of analytics
  • Monitor effectiveness of analytical models and ensure accuracy of all data from source to final deliverable through a systematic data quality control process
  • Work in complex data environment comprising several heterogeneous internal and third party data sources, manipulate large data sets and navigate a variety of servers, data types, and data structures to complete statistical and other analyses
  • Work on self-serve delivery, automation, and maintenance of reports and visualizations
  • Work with IT partners (e.g., data warehousing team) to design optimal data architecture for analytics and BI tools


Qualifications:

  • At least 1 year of experience in marketing/sales analytics, segmentation, and forecasting
  • At least 1 year of experience with a statistical analysis tool like R, SAS or SPSS
  • At least 1 year of experience performing data management, mining, and manipulation
  • Proficiency in a wide range of analytical methods including multivariate, time series, classification, and machine learning  
  • Working knowledge of SQL and relational data model
  • Working knowledge of at least two technologies: Python, Big Query, Google Analytics, Spotfire, and/or Tableau
  • Ability to translate quantitative results into clear and concise business presentations/reports using compelling data visualization techniques
  • Able to write code to query and transform both unstructured and structured data
  • Proven track record of identifying and highlighting key insights, signals, and trends deep within the underlying data
  • Bachelor’s degree in Statistics/Mathematics,Econometrics/Economics, Engineering/Computer Science, Business/Finance, or related quantitative field
  • Advanced degree a plus

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