Data Scientist

 

 

Job Description

Overview

The primary function of the Data Science Analyst are the following:

Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

Develop custom data models and algorithms to apply to data sets.

Develop processes and tools to monitor and analyze model performance and data accuracy.


Skills and Qualifications

  A Degree holder in Statistics, Mathematics, Computer Science or another      quantitative field, and is familiar with the following software/tools: Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.

At least 1 year relevant experience in using statistical computer languages (R, Python, SQL,etc.) to manipulate data and draw insights from large data sets.

  Experience working with and creating data architectures.
  Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

  Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.

  Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering,decision trees, neural networks, etc.
Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights,etc.

Experience with distributed data/computing tools: Map/Reduce, Hadoop,Hive, Spark, Gurobi, MySQL, etc.

Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.

Principal Duties

Work with stakeholders throughout the organization to identify opportunities for leveragin company data to drive business solutions.
Mine and analyze data from DataLake/s and Data Warehouse/s to drive optimization and improvement of product development, marketing techniques, business strategies and other initiatives.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.

Develop custom data models and algorithms to apply to data sets.
Use data analytics modeling to increase and optimize customer experiences, revenue generation,ad targeting and other business outcomes.
Develop company data model testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.

Develop processes and tools to monitor and analyze model performance and data accuracy.
 Perform other related tasks as required.