Summary The Data Scientist role has a strong background in data analysis, statistical modeling, and machine learning. You will be responsible for extracting insights from large datasets, developing predictive models, and providing actionable recommendations to drive business decisions. The Data Scientist will work with the Operations and Plant Excellence teams to implement the solutions they create for the daily manufacturing process. Solutions will be focused on Scheduling, Right First Time, Yield, etc. With your expertise the Operations Research Team will help drive improved operational performance across SQCDP. Essential Functions - Extract and manipulate datasets from different data sources such as databases, text files, etc.
- Develop and implement machine learning models and algorithms.
- Research and develop heuristics used to solve daily operating problems.
- Create data visualizations and dashboards to communicate findings to stakeholders.
- Work with operations teams and other non-technical stakeholders to implement solutions.
- Works on multiple tasks/projects as team member.
- Provides input to business requirements for the design of solutions.
- Interprets business requirements and determines optimum data science solutions to meet needs.
- Identifies and provides input to new technology opportunities that will have an impact on the PCC Metals’ systems.
- Transforming, integrating, and presenting data for analysis
- Provides input to the development of information quality metrics.
- Integrate R and Python into BI objects to provide analytics beyond what BI tools are capable of.
- Define and evaluate performance metrics to measure the impact of operational improvements
Qualifications Competencies - Highly motivated, independent, attention to detail, big-picture thinker, innovative, communicator.
- Strong written and verbal communication skills – ability to effectively collaborate with other Analysts as well as non-technical personnel to move projects forward.
- Strong knowledge of machine learning techniques and algorithms.
- Knowledge of basic data modeling principles (star schema, relational databases, etc.)
- Willingness to observe and learn manufacturing processes.
- Proficient in statistical analysis.
- Ability to design a solution architecture in a constrained environment (limited tools available, isolated networks, etc.) and see it through from development through deployment and sustainment.
- Use “design thinking” to solve operational challenges in a way that ensures adoption by operators and managers alike.
Education and Experience - Bachelor’s degree in statistics, mathematics, computer science, or related field.
- Master’s degree preferred.
- 2+ Years of Analytics Domain experience.
- Experience with cloud technologies desirable. AWS preferred.
Tools Programming Languages Business Intelligence tools - Power BI (preferred), Tableau, or Shiny (preferred)
Data Manipulation - SQL (required), Spark, Pandas, or dplyr
General Software - Microsoft Word, PowerPoint, and Excel
Additional Notes Job Dimensions Work Environment – Office based, with a need to spend time on a manufacturing shop floor. |