Known for our innovative components, Mitsubishi Electric Automotive America manufactures autonomous-ready infotainment and ADAS solutions, premium audio systems, high-definition displays, and powertrain electronics for standard, electric, and hybrid vehicles. Since 1979 we have served the major automotive, heavy-duty truck, and coach manufacturers across the US, and continue to grow each year! Be a part of a select team that is making a real impact on the automotive mobility of tomorrow!
Compensation Data
$116,621 to $129,579 Annually
Variable Bonus Potential
401K Savings Plan with Company Match
Full Benefit Enrollment Options
Summary
Mitsubishi Electric Automotive America has an opportunity for an experienced Application Engineer, focused on Data Science, to join our team working at the Northville, Michigan facility (Detroit area). The Engineer will Develop and deploy applications in cloud settings. Working along with cloud service providers and other technologies to build, test, and deploy software that complies with organizational needs.
Responsibilities
Primary functions for this role will include but are not limited to the following
Data Wrangling: data cleaning, preprocessing, post processing, transformation, and aggregation
Solid foundation in probability theory, hypothesis testing, linear algebra, Bayesian statistics.
Advanced statistical modeling: Familiarity with time series analysis, forecasting, and casual inference techniques.
Programming in Python (including libraries: Pandas, Scikit-learn, Numpy)
Data Visualization: creating clear and insightful visualizations to communicate data insights effectively. Utilzing tools like Tableau or Power BI, Matpotlib, seaborn.
Coordinate with cross-functional teams to evaluate, design, implement, and integrate customer requirements.
Design, implement and maintain Continuous Integration / Continuous Deployment pipeline solutions.
Document and track issue, maintain the list through the life of program.
Stay up to date with new technologies and trends in cloud computing.
Support requirement definition for Azure and AWS architectural standards for cloud infrastructure systems.
Create container images and run containerized applications such as Docker.
The above description represents the most significant essential duties of this position. The position does not exclude other occasional work assignments not mentioned.
Qualifications
If you meet some but not all of the listed qualifications, you should submit your profile to be considered by the hiring team. Not all qualifications are likely to be met by a single applicant. We will look forward to viewing your submittal.
BSEE, BSCS or equivalent training in Computer Science, Computer Engineering, Information Technology, or similar field of study.
Minimum of 6 years of experience with ML and data wrangling.
Minimum of 4 years of experience with AWS integration and pipeline setup.
Minimum of 4 years of experience working with Azure & DevOPs, Socket Programming, and other cloud-based services.
Strong Familiarity with the basics of cloud architecture.
Knowledge of cloud computing systems like Amazon, Azure, or Google Cloud.
Additional Preferred Qualifications
MS level education or equivalent training.
Experience working on Big Data and Data Science.
Experience working on Cyber Security.
Experience working on network programming and management.
Understand, maintain, and execute software changes using .NET framework.
To the extent that such laws prohibit discrimination and harassment, MEAA shall not discriminate against any applicant, associate, vendor, contractor, customer, or client on the basis of age, race, color, religion, creed, ancestry, national origin, citizenship status, sex, gender, sexual orientation, gender identity, gender expression, pregnancy, marital status, physical or mental disability, medical condition (as defined by applicable law), genetic information, military or veterans' status or any other basis prohibited by law.
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Applicants with a disability who need assistance with the application process may contact Human Resources by email at [email protected] ([email protected]) or by calling 1-800-275-5077.
