Data Analyst

JOB DESCRIPTION

The Data and Analytics team works with people across the organization to identify, assess, and solve real business problems by analyzing all available data, including enterprise, connected product, and publicly available datasets, to create and discover meaningful insights.

As a data analyst, you will:

• Define and refine the problem to solve working alongside business and technology teams, asking the right questions to develop and drive purposeful analytics
• Identify, collect, and clean available data to prepare for analysis
• Perform exploratory data analysis and statistics to provide initial insights
• Determine the appropriate analytics approach when developing and applying models
• Deploy analytics product, automating data pipeline
• Communicate the analysis and its finding in clear language and with data visualizations, assist in how to interpret and leverage the analysis, and help others understand its implications

Here are examples of analytics performed by our team.

• Provide statistically reasonable expectations of future part number consumption to help plant-level buyers, purchasing managers, and plant managers plan their inventories, using historical ERP and external macro data
• Identify high-risk purchase items that have an adverse impact on our ability to execute, suggesting more realistic costs and lead times to update ERP systems
• Quantify the lifecycle of market-leading product lines , connecting different data sets to recreate a digital footprint and discover previously unattainable insights
• And many more

SUGGESTED QUALIFICATIONS

• Undergraduate degree in a quantitative discipline (e.g., Business Analytics, Computer Science, Data Science, Economics, Industrial Engineering, Math, Statistics)
• Two or more years of relevant work experience, mining data as a data analyst or scientist or in a business role with a heavy focus on analytics or statistics
• Strong analytical, quantitative, and problem-solving skills
• Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
• Experience with different methods for dealing with large, multi-dimensional data sets, including relational databases, SQL, and ETL
• Proficiency in one or more programming language (e.g., Python, R, SAS) or other tools appropriate for large-scale data preparation and analysis (i.e., not Microsoft Excel)
• Willingness to learn how our operations and supply chain teams work
• Strongly preferred: Familiarity with a manufacturing company's daily operations and related data sources, including ERP systems and related table structures
• Ability to work collaboratively with other data scientists, analysts, and businesspeople
• Ability to work independently, exercise initiative, and follow through to accomplish tasks
• Ability to manage adjusting priorities and work on multiple projects simultaneously while addressing ad hoc data requests