Data Scientist

Job Description

• Work with stakeholders throughout the organization to identify opportunities for leveraging enterprise data to drive business solutions.
• Mine and analyze data from enterprise 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.
• Ready to fully implement solutions, and test them effectively.
• Use predictive modeling to increase and optimize user experiences, process automation, recommendations and other business outcomes.
• Develop company A/B 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.
• Build data systems and pipelines
• Conduct complex data analysis and report on results
• Prepare data for prescriptive and predictive modeling

Job Requirements

• Strong problem solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• We’re looking for someone with 3-5 years of experience manipulating data sets and building statistical models, has a degree in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
  • Coding knowledge and experience with several languages: R, Python, Java, etc.
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • Experience querying databases and using statistical computer languages: R, Python, SLQ, 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: Cognos, Business Objects, Tableau, etc.