Sales Data Science / Analyst / Statistician

Sales Data Science / Analyst / Statistician

We are looking for a Data Scientist who will support our product, sales, leadership and marketing teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.

Responsibilities for Data Scientist

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Collect, analyze, perform statistical analysis and interprets data
• Create algorithms based on findings
• Set-up predictive models

Qualifications for Data Scientist

• Strong problem-solving skills with an emphasis on product development.
• Experience using statistical computer languages (Python, Spark, Scala)
• Must understand Vector program
• Statistical theories and methodologies
• Data mining
• Understanding of distributed computing
• Understanding of No SQL databases
• Effective communicator and storyteller of data

Experience and Education:

We’re looking for someone with 3-5 years of experience manipulating data sets and building statistical models, has a Bachelors in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:

• Experience querying databases and using statistical computer languages: Python, SLQ, etc.
• Experience using web services: Spark, DigitalOcean, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

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