The Ingredion Digital Transformation team has an outstanding opportunity for a highly motivated and dynamic college student to join the organization for an internship during the summer of 2022. In this role, you will perform statistical data analysis, data mining and optimizations using multiple tools and techniques to provide insights of manufacturing operations data. We are looking for someone who has a strong initiative to improve status-quo and incorporate change in a dynamic work environment. We hope that this person can also demonstrate the capacity to take on problems through creative, innovative solutions and challenge traditional methods of accomplishing tasks.
As the Data Science Intern, your responsibilities will include:
- Supporting the digital CoE team by developing innovative methods to find correlations between various manufacturing operations measures
- Developing predictive models that help achieve business targets using R, SAS and Python
- Designing and implementing new multivariate methodologies to solve practical business problems
- Finding patterns and insights in unstructured data
- Employing advanced data modeling and forecasting techniques to explore strategic business opportunities and to prescribe actionable recommendations to leverage those opportunities
- Developing an understanding of Operational team requirements from plant operations information in order to align modeling to provide actionable information
- Build links with key decision-makers and internal partners
- Visualizing and reporting insights creatively in a variety of formats to various partners
The Data Science Intern is well suited for you if you:
- Being a self-starter with the ability to be productive independently and are able to handle multiple projects
- Are organized, detailed, and service oriented with a strong character and leadership style
- Are technically proficient and utilize technology in creative problem-solving ways to influence strategic decision-making
Qualified candidates will have:
- Progress towards a master’s degree program in Computer Science, Statistics, Mathematics or a related field with a minimum GPA of at least 3.0/4.0 preferred
- Ability to work 40hrs per week during the summer internship term
- Demonstrated programming skills with R, SAS, Python or Java
- Validated ability to sift through data, identify critical information, develop hypotheses, perform rigorous analyses and make recommendations to broader audiences
- A deep understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering and classification techniques and recommendation and optimization algorithms
- Ability to easily understand the complex algorithm and logic to process data
- Familiarity with Microsoft Azure platform
- A methodical and a detail-oriented way of thinking
- Good communication skills (both oral and written)
- Reliable transportation required to get to and from facility each work day
To be eligible for consideration, candidates must:
- Currently possess unrestricted authorization to work in the United States. Ingredion does not intend to sponsor work visas with respect to this position or to provide this position as OPT or CPT.
- Be a currently enrolled student in a Master’s Degree Program. If currently enrolled in an undergrad status, must have completed at least two years of coursework with status as a sophomore, junior or non-graduating senior.
- If you have completed your degree, please consider other opportunities with Ingredion, posted at www.ingredion.com/careers.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Ingredion provides accommodations to job applicants with disabilities throughout the hiring process. If a job applicant requires an accommodation during the application process or through the selection process, we will work with the applicant to meet the job applicant’s accommodation needs.