TEAM YOU’LL BE JOINING:

• Leader in the automotive and industrial industry. Manufacturing of OEM and Industrial OEM
• Technology focused organization who is on the cutting edge of manufacturing automation/digitization
• North American Division near $2.5bil with a much larger global footprint

WHAT THEY OFFER YOU:

• Team leadership is very open to new ideas including tool/technology selection
• This is a dispersed team, but a very cohesive unit
• North American Leadership team is tenured and pushes for their employees to have the best possible work environment
• Highly visible position within the IT Department with direct learning opportunity from a strong team including Data Engineers

WHY THIS ROLE IS IMPORTANT:

• Lead discovery processes with business stakeholders to identify opportunities and business problems and framing them into an IT data science/ advanced data analytics project initiative.
• Perform data cleansing using data processing and statistical software packages.
• Perform data quality assessments and statistical testing to verify data quality and data integrity
• Exploratory data analysis for extracting business insights from large volume of data using data science toolkits and statistical packages.
• Using data processing and statistical software packages.
• Perform data quality assessments and statistical testing to verify data quality and data integrity
• Exploratory data analysis for extracting business insights from large volume of data using data science toolkits and statistical packages.

THE BACKGROUND THAT FITS:

• Master’s degree in Applied Mathematics, Statistics, Machine Learning, Electrical Engineering, Computer Science/Information Systems or related fields or MBA with quantitative focus.
• 2-5+ years of professional Data Science Experience
• Must have experience in Python and SQL (R preferred)  
• High-level experience with the use of opensource statistical and machine learning packages (Numpy, Pandas, Scikit-learn, Stats Tool, etc.)
• Ability to demonstrate familiarity with data analysis and statistical modeling
• Knowledge of visualization tools and libraries