Data Science Specialist

Job Description:

Data Science Specialist

Collaborate with Innovative 3Mers Around the World

Choosing where to start and grow your career has a major impact on your professional and personal life, so it’s equally important you know that the company that you choose to work at, and its leaders, will support and guide you. With a wide variety of people, global locations, technologies and products, 3M is a place where you can collaborate with other curious, creative 3Mers.

This position provides an opportunity to transition from other private, public, government or military experience to a 3M career.

The Impact You’ll Make in this Role
The person hired for this position will support digital transformation for the Transportation & Electronics Business Group Laboratory. The person in this position will work closely with colleagues in the Systems and Modeling Group, manufacturing, and division partners. The ideal candidate will perform well in a fast-paced, cross-functional environment and is able to manage multiple projects effectively while collaborating with personnel in divisions, manufacturing, and corporate research labs. It is expected that this statistician will be responsible for applying statistical methodologies and machine learning techniques to design experiments, analyze complex data sets, and provide actionable insights to enhance business operations. Your role will involve developing predictive models, designing and analyzing experiments, and collaborating with teams to solve challenging business problems using data.

As a statistician, you will have the opportunity to tap into your curiosity and collaborate with some of the most innovative people around the world. Here, you will make an impact by:

• Design of Experiments (DOE): Develop and implement experimental designs to optimize processes, understand variability, and determine key factors that impact outcomes.
• Data Analysis: Use advanced statistical techniques (e.g., regression analysis, ANOVA, hypothesis testing) and machine learning algorithms (e.g., random forests, neural networks, support vector machines) to analyze data and extract meaningful insights.
• Model Development: Build and deploy predictive models using statistical or machine learning techniques to address business challenges and drive performance improvements.
• Data Preprocessing: Clean, preprocess, and transform raw data for analysis, ensuring high-quality datasets for both statistical and machine learning models.
• Collaboration: Work closely with cross-functional teams (e.g., engineering, marketing, operations) to understand data requirements and ensure alignment with business goals.
• Reporting and Visualization: Create clear, concise reports and data visualizations to communicate findings and recommendations to both technical and non-technical stakeholders.
• Optimization: Leverage DOE principles and machine learning models to optimize systems and processes, continuously improving efficiency and outcomes.
• Research and Innovation: Stay updated with the latest advancements in statistical methods, DOE techniques, and machine learning technologies to incorporate innovative solutions into analyses.

Your Skills and Expertise 

To set you up for success in this role from day one, 3M requires (at a minimum) the following qualifications:

• Master’s degree in Statistics, Data Science, Mathematics, Engineering (completed and verified prior to start)
• Three (3) years of industry and statistics experience in a private, public, government or military environment

Additional qualifications that could help you succeed even further in this role include:

• Industry experience of 2 or more years in related fields.
• PhD in Statistics, Data Science, Mathematics, Engineering, or a related field.
• Strong experience in Design of Experiments (DOE), including creating and analyzing factorial designs, definitive screening designs, response surface methodology (RSM), and optimization techniques.
• Hands-on experience with machine learning algorithms (e.g., regression, classification, clustering, and neural networks)
• Proficiency in statistical software (e.g., R, SAS, Minitab, JMP) and programming languages (e.g., Python, MATLAB).
• Solid understanding of data manipulation, exploratory data analysis, and feature engineering techniques.
• Strong analytical skills, with the ability to work with large and complex datasets.
• Experience with model evaluation and validation techniques, including cross-validation and hyperparameter tuning.
• Ability to communicate complex statistical and machine