MACHINE LEARNING ENGINEER (REMOTE) #00081049

Vice Chancellor- Finance & Operations

We are seeking an experienced and highly motivated data and machine learning professional to advance predictive analytics at Missouri S&T. The Machine Learning Engineer will be instrumental in the building of data, statistical modeling, and predictive reporting capacity of the university. In addition to supporting the general data operations of S&T, the ML Engineer will have a significant emphasis on multivariate descriptive and predictive modeling related, but not limited, to student retention, attrition risk, enrollment yield and other predictive programs. This position will build processes and statistical models that integrate student, institutional, and peripheral data with other sources of data.  Working closely with partners, this individual will troubleshoot barriers to the collection and integration of datasets needed to perform modeling. Uses expert statistical methods to analyze data and generate useful reports, models, and findings.

The ML Engineer may be required to come to the S&T campus at their own expense for meetings, training, troubleshooting, etc.  The rest of the time the position will work remotely.

Key Responsibilities

• Work with business stakeholders to gather requirements and create technical specifications for solutions
• Uses expert statistical methods to analyze data and generate useful reports, models, and findings
• Develops data and analytics automation processes related to models and stakeholder information needs
• Develops, prepares, delivers, and interprets institutional data sets
• Prepares actionable reports, presentations and proposals that are easy to read and interpret
• Partners with data source custodians to identify data sources of truth, improve data quality, and extend depth of data available to inform models and institutional research activities
• Recommends enhancements to current systems and processes as related to modeling and outcomes activities
• Maintains documentation for all data management, analysis, and reporting activities
• Serves as the subject matter expert about data quality, task suitability, and availability
• Collaborate with other analyst and developers to integrate predictive modeling into existing BI solutions
• Stay current with the latest developments in the Microsoft data stack and other related technologies

Bachelor's degree or an equivalent combination of education and relevant experience, and at least 4 years of experience from which comparable knowledge and skills can be acquired is necessary

• Master's degree in mathematics, computer science, applied statistics, economics or equivalent or bachelor’s degree in a social science and experience in computer science or data analytics preferred.
• At least 5 years of experience from which comparable knowledge and skills can be acquired is necessary.
• 2-3 years of experience in data analysis/mining and reporting preferred. Research support or institutional research experience.
• Knowledge of higher education student retention/attrition theories preferred.
• Broad knowledge of and experience in SQL and query-based software packages.
• Experience with statistical and machine learning libraries of Python preferred.
• Broad knowledge of and experience in visualization techniques and software (e.g., PowerBI, D3) preferred.
• Solid knowledge of multivariate and model-based statistical methods.
• Self-motivation and discipline to regularly set and achieve work goals required.
• Experience with the Microsoft data tools (Azure, Fabric, Power BI, Synapse, Data Factory).
• Excellent communication skills and ability to work collaboratively with stakeholders and team members.

The anticipated hiring range for this position has been established as $68,200-$85,000 annually. 

  
Salary is determined by a variety of factors, including but not limited to, the individual’s particular combination of education, skills, and experience, as well as organizational requirements. 

Your total compensation goes beyond the number on your paycheck. The University of Missouri provides generous leave, health plans, and retirement contributions that add to your bottom line. 
Grade: GGS 12
University Title: DATA ANALYST II 
To review the University of Missouri’s Staff Compensation Structure you can view the Job Code detail page . Internal applicants can determine their university title by accessing the Talent Profile tile in myHR.

Applications will be accepted until this position is filled.

This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, paid time off, short- and long-term disability, paid parental leave, paid caregiver leave, and educational fee discounts for all four UM System campuses.  For additional information on University benefits, please visit the Faculty & Staff Benefits website at https://www.umsystem.edu/totalrewards/benefits . 

Values Commitment
We value the uniqueness of every individual and strive to ensure each person’s success. Contributions from individuals with diverse backgrounds, experiences and perspectives promote intellectual pluralism and enable us to achieve the excellence that we seek in learning, research and engagement.  This commitment makes our university a better place to work, learn and innovate.

In your application materials, please discuss your experiences and expertise that support these values and enrich our missions of teaching, research, and engagement.

Equal Employment Opportunity

The University of Missouri System is an Equal Opportunity Employer. Equal Opportunity is and shall be provided for all employees and applicants for employment on the basis of their demonstrated ability and competence without unlawful discrimination on the basis of their race, color, national origin, ancestry, religion, sex, pregnancy, sexual orientation, gender identity, gender expression, age, disability, or protected veteran status, or any other status protected by applicable state or federal law. This policy applies to all employment decisions including, but not limited to, recruiting, hiring, training, promotions, pay practices, benefits, disciplinary actions and terminations. For more information, visit https://www.umsystem.edu/ums/hr/eeo or call Human Resources at 573-341-4241.
To request ADA accommodations, please call the Office of Equity & Title IX at 573-341-7734.