Essential Duties and Responsibilities include the following.

• Identify and implement strategies to leverage various large data sources for purposes of improving assortment availability
• Collect, analyze, and interpret information from multiple data sources identifying actionable insights that create efficiencies and generate revenue.
• Fully understand and support existing machine learning processes and provide development support for enhancements
• Build new predictive models and machine-learning algorithms for second-level analytics and assortment related processes
• Develop reports and/or presentations leveraging data visualization tools that clearly and concisely communicate analytical findings and recommendations to key stakeholders.
• Analyze customer sales, transaction, and vehicle related data to identify trends and patterns for use in improving store assortments
• Leverage analytical tools (SQL, Python, R) and data mining techniques to perform advanced data manipulation and extract insights from large databases.
• Support ad hoc data analysis as requested.
• Demonstrated desire for continued learning and keeping up with latest techniques in the field of statistics, predictive analytics, operations research or related focuses.
• Provide guidance and recommendations to leadership team in areas of analytics and data science
• Work within a team environment that practices agile methodologies
• This job requires occasional late hours to attend video conferences with fellow team members in United States
• Other duties may be assigned.

Required Qualifications
Capable of performing the duties listed above. Proven understanding of latest modeling and forecasting techniques. Skilled with python programming techniques, unit testing, documentation. Familiarity with AWS, Notebooks, Hadoop, EMR and S3 necessary. Familiarity with agile project management a plus.

EDUCATION and/or EXPERIENCE
Bachelors or Masters Degree in Data Science or another quantitative field. Minimum of 2 years of work experience in a data science related.