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Global Data & Analytics Group is a cross-functional team within the Process Research group at Guardian Glass. We are on the front lines of projects that impact the operations and business of Guardian Industries manufacturing assets. We employ Machine Learning, Artificial intelligence, Optimization, Process Engineering, and IoT technologies to improve efficiency of Guardian’s manufacturing processes. Examples of the challenges our group tackle are opportunities to optimize the existing operations, work closely with process research and operations teams to determine what process settings drive certain manufacturing results and to improve operations or predict future behaviors of product as it moves through the manufacturing. GD&A group is that focuses on applying advanced quantitative methods to solve a wide variety of challenging operations problems.
Guardian has an immediate opening for a Data Scientist based out of Carleton, MI. Come join a growing team dedicated to identifying, developing, refining, and deploying data science solutions in glass making, coating processes, and business forecasting. As a Data Scientist, you will use machine learning techniques to gain and share new insights, develop predictive tools, and improve process control and predictability. You will be responsible for working closely with key stakeholders and data engineers to efficiently identify and implement improvements to data infrastructure for downstream analytics needs. you will determine the right models to use for various process applications from ideation, proof-of-concept through design of applications, as well as monitor and improve deployed operational-real-time models. You will keep Guardian current with state-of-the-art machine learning software and hardware in the cloud and on-premise and pursue continuous self-training and train others across the organization. You will gain exposure to senior leadership as you showcase your results to key stakeholders in the business, demonstrating the superior value of your work. You will report into the R&D Group Leader of Process Research & Data Analytics. Our group of highly skilled, enthusiastic data scientists and operations research engineers is redefining what’s possible for Guardian by utilizing the massive amount of process data to transform operations and research and development. We invest in our team by encouraging attendance at industry conferences and ongoing education opportunities enabling them to stay on the dynamic ever-changing data science landscape and bring new methods and techniques to their projects.
What You Will Do In Your Role
- Develop a strong understanding of the operations and business processes and identify possible opportunities that add value
- Apply machine learning algorithms to perform analysis, create predictive models, visualize data, and drive projects through to delivery toward the solution of operations problems
- Interact with business and manufacturing SMEs to identify requirements and propose solutions
- Demonstrate intellectual curiosity to research and identify new modeling technologies/methodologies/software packages to improve the current modeling processes
- Continuously scan and test new data sources, tools, and analytical techniques and partner with leading institutions and experts to contribute to our portfolio of next-generation analytics projects
- Interface with key stakeholders and technical experts to ensure hardware and software support for data analytics is maintained
- Analyze large complex time series datasets to extract useful patterns to deliver business insights and communicate results to key decision makers
- Issue reports detailing tool development (including unsuccessful approaches), quality assurance actions performed, results, etc.
- Work with data engineers to improve functionality in data systems (e.g., data reliability, efficiency, usability, and quality) and improve downstream data analysis capabilities
- Work with various functional teams; owning end-to-end solution development and scaling focused on operations challenges
- Rapidly design, prototype, and test many possible hypotheses. Further, focus on building minimum viable products toward solving most of the issue instead of “perfecting” the solution, unless critical to safety
- Engage with internal customers – operations teams and process SME’s – to leverage your critical thinking skills to apply data science modeling solutions
- Possess strong communication skills for technical and non-technical audience. Solid technical writing and presentation skills
- Demonstrate strong data-driven storytelling to present to stockholders
- Leverage analytical rigor and statistical methods, and creativity to solve problems
- Research and implement advanced Machine Learning techniques to solve operation and business opportunities; move from proof of concept to minimum viable product efficiently
- Open to learn continuously and apply what’s learned in practical applications
- Leading and working on multiple projects at the same time and switching priorities as the business needs require
- Employ visualization, reporting and other tools to improve the ways in which teams access various datasets
- Strong data-driven storytelling to present to stockholders
The Experience You Will Bring
- Bachelor’s/Master’s degrees with two (2) or more years’ experience in a quantitative field (Data Science, Engineering, Statistics, Computer Science, Physics, Operational Research, Economics, or equivalent)
- Two (2) or more years’ experience of applying ML to solve complex problems for applications
- Experience applying knowledge for a variety of predictive, machine learning, and artificial intelligence techniques (classification, predictive, artificial neural networks, etc.) and real-world applications such as computer vision
- Experience to include advanced knowledge of statistical techniques and concepts (probability, statistical tests, multi-variate regression, etc.) and experience with applications
- Two (2) or more years’ experience with hands-on experience in programming with Python and machine learning packages (Tensorflow/PyTorch, Keras, Scikit-learn, Pandas, Numpy, Plotly, Plotly Dash, Streamlit, etc.)
- Fluent with SQL
- Experience with project management (e.g., Agile) and executing projects that require cross-functional
- Experience using concepts of power analysis, hypothesis testing, inference, and DOE
- Experience with various computing infrastructures and technologies e.g., AWS, GPU, Linux, GIT, etc.
- Willing & able to travel up to 10% of the time
What Will Put You Ahead
- Ph.D. degree in a quantitative field (Data Science, Engineering, Statistics, Computer Science, Physics, Operational Research, Economics, or equivalent)
- Working knowledge of glass manufacturing processes and/or vacuum coating
- Experience in process operations analytics and manufacturing optimization
- Knowledge of tools such as Spark, Hadoop, Pig, Kafka, Kinesis, Docker, Snowflake, Amazon SageMaker, AWS, Azure
- Knowledge in FinTech
- Experience with UI/UX
Our goal is for each employee, and their families, to live fulfilling and healthy lives. We provide essential resources and support to build and maintain physical, financial, and emotional strength – focusing on overall wellbeing so you can focus on what matters most. Our benefits plan includes – medical, dental, vision, flexible spending and health savings accounts, life insurance, ADD, disability, retirement, paid vacation/time off, educational assistance, and may also include infertility assistance, paid parental leave and adoption assistance. Specific eligibility criteria is set by the applicable Summary Plan Description, policy or guideline and benefits may vary by geographic region. If you have questions on what benefits apply to you, please speak to your recruiter.
At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate’s knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.