Position Summary:

If you are one to immerse yourself in technology and are forward thinking when it comes to building solutions, why not join a team that shares those same traits? At Pax8, we embrace technology and have our teams explore what it has to offer. In an ever-changing industry, you will take us to new heights through the means of machine learning and AI.  

As a Data Scientist, you will explore and implement various machine learning concepts and AI models to bring enhancements to the Pax8 marketplace. 

Aimed to effectively impact our customers’ experience, you will bring your existing knowledge and experience of chatbot, customer scoring and other marketplace enhancement features. Your skills with Python and SQL will be necessary to appropriately apply these features.  

Meet the team and hear what they have to say about our Product & Engineering group: Meet the Team

Essential Responsibilities:

• Develops comprehensive data science solutions
• Develops machine learning infrastructure, deployment, and monitoring
• Mentors junior level Data Scientists
• Includes testing in all aspects of the development process
• Creates descriptive reports and visualizations detailing the performance of advanced analytics projects
• Analyzes potential problems and finds solutions to pressing data issues
• Participates in on-call rotation

Ideal Skills, Experience, and Competencies:

• At least two (2) to six (6) years of relevant data science experience
• Intermediate experience with the Python data science stack (pandas, scikit-learn, keras, etc.)
• Advanced experience with SQL
• Moderate experience with Apache Spark or other distributed processing engines
• Intermediate experience with supervised and unsupervised machine learning models
• Intermediate experience with statistical methods
• Effective problem solving and troubleshooting abilities
• Ability to consistently achieve results, even under tough circumstances

Required Education & Certifications:

• B.A./B.S. in related field or equivalent work experience
• M.S./M.A. in related field or equivalent work experience preferred

Compensation:

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