Job Overview

Data Scientist II

Areas of key responsibilities:

In-depth Analysis, PCA

• Gather business requirements and then translate into analytics objectives and analysis plan that you and the team can begin working towards
• Analyze complex business issues and effectively communicate meaningful insights based on data trends / patterns found in data
• Build clean, concise and digestible visualizations and dashboards for the team and/or client to use and gain insight from
• Conduct in-depth analysis and post-campaign analysis to evaluate ESPs performance & ROI, and provide recommendations for improvement

Machine Learning & other POC

• Build machine learning models such as clustering for member segmentation and predictive models to uncover opportunities for maximizing customer wallet share (e.g. upsell/cross-sell/retention)
• Develop and implement new analytical methodologies and techniques for clients
• Continue to develop and build-out the best practices for analytics and share learnings with peers
• Contribute to the evolution and internal innovation of our Analytics and Data Science capabilities, toolsets and knowledge-base

Background and Experience:

What are the requirements for this position in terms of education, knowledge and experience in order to accomplish the responsibilities and deliver the desired end results?

Minimum Qualifications:

• Bachelor’s degree in Business, Analytics, Computer Science, Management Information Systems, Statistics or related field
• Fluency in SQL
• Experience with at least one core statistical programming language (e.g. R, python)
• Comprehension of data visualization best practices
• Experience with data visualization tools (e.g. Tableau, PowerBI, Domo, Looker)
• Strong Microsoft Suite skills, especially with Excel & PowerPoint

Preferred Qualifications:

• Ideally 3-5 years of relevant analytical experience
• Prior experience building predictive modelling and member segmentation models
• Experience and understanding of A/B and multivariate testing best practices and application
• Experience with AWS technology stack including Redshift
• Experience with version control and code hosting services (e.g. Bitbucket, Github)
• Comfortable synthesizing and presenting technical concepts and insights

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