About The Position:
The Ameren Innovation Center is located at the University of Illinois’ Research Park. Its mission is to support Ameren’s innovation initiatives and contribute to the digital transformation occurring throughout the organization.
The center is a modern workspace that encourages collaboration and creative thinking in an effort to solve exciting and meaningful challenges. Groups of talented, multi-disciplinary students work in multi-disciplinary teams with direction from full-time staff to achieve this vision.
As a Data Scientist at Ameren’s Innovation Center, the chosen candidate has the opportunity to transform the future of Ameren's data analytics practices through creatively translating, consuming, extracting, and visualizing data.
The Data Scientist will work as part of the Innovation Center’s team to design and implement processes related to predictive/analytical modeling, data mining and research on large scale, complex data sets with the goal of driving business decisions.
This position is expected to accomplish these tasks through a combination of self-directed work and support from the student workforce.
The Data Scientist will have the opportunity to mentor, guide and collaborate with internal and vendor teams. The chosen candidate will gain experience in managing the lifecycle of data analytics projects and will communicate findings to both stakeholders and executive leadership.
Key responsibilities include:
• Creating valuable, transformative business strategies through the measurement, manipulation, reporting, and dissemination of broad sets of data.
• Executing analytical projects as an individual contributor.
• May guide, mentor and develop others as they build knowledge and skills in analytics.
• Developing new predictive/analytical modeling methods as required and apply state-of-the-art, advanced analytic and quantitative methodologies.
• Working with the corporate data teams to identify data relevant and data strategies.
• Contributing to predictive/analytical modeling architectures, modeling standards, reporting, and data analysis methodologies.
• Contributing to recommendations on predictive/analytical modeling products, services, protocols, and standards in support of business processes.
• Collaborating with unit managers, end users, development staff, and other stakeholders to enhance operations by supplying data analytics insights into business processes.
• Applying quality assurance best practices for predictive modeling/analytics services.
• Adhering to change control and testing processes for modifications to analytical models.
• Collaborate and leverage the skills within the Data Analytics team to achieve desired results and increase adoption of analytics across the enterprise.
• Research trends in forecasting including methodologies and data availability.
• Research mathematical models, methods, and best practices for data architecture and develop practical tools based on research findings.
Bachelor's Degree in a technical discipline (e.g., computer science, engineering, mathematics, statistics or related field) with three or more years of professional-level experience contributing individually or as part of a team to manage data analytics projects required (relevant professional-level internship experience will be considered);
Advanced degree in a technical discipline (e.g., engineering, mathematics, statistics, finance/economics, business management, or related field) with one or more years of relevant professional-level internship experience required.
Three or more years of technical experience in predictive analytics, machine learning, optimization, and fluency in technologies such as R, Python, SQL, AWS, Tableau, SAS, Power BI, etc. preferred.
In addition to the above qualifications, the successful candidate will demonstrate:
• Knowledge of data mining and predictive modeling tools such as SAS, SPSS, etc.
• Strong understanding of predictive/analytical modeling techniques, theories, principles, and practices.
• Specific experience in more than one of the following - applying decision trees, logistic regression, factor analysis, statistical modeling, text mining and other advanced analytic techniques.
• Ability to conduct research into predictive/analytical modeling issues, practices, and products as required.
• Strong familiarity and experience with data preparation and processing – such as assessment of data quality, new variable creation, variable selection, etc.
• Proficient in assessing data needs for specifics analysis projects.
• Ability to interpret the results of analytical work, assess its relevance to real world business results, and effectively communicate the information in plain language that is readily understood by business line leaders.
• Proficient in working on multiple projects simultaneously, often with tight deadlines.
• Strong intrinsic problem-solving skills, ability to structure and solve problems, and conduct and interpret analysis independently with demonstrated analytic and quantitative skills.