International paper (nyse: ip) is a leading global supplier of renewable fiber-based productsWe produce corrugated packaging products that protect and promote goods, and enable worldwide commerce, and pulp for diapers, tissue and other personal care products that promote health and wellnessHeadquartered in memphis, tenn., we employ approximately 38,000 colleagues globallyWe serve customers worldwide, with manufacturing operations in north america, latin america, north africa and europeNet sales for 2021 were $19.4 billionIn russia, we have a 50/50 joint venture, ilim group, the country`s largest integrated manufacturer of pulp and paperAdditional information can be found by visiting internationalpaper.com.
Manufacturing data analyst
The primary role for a manufacturing data analyst is to reduce manufacturing cost, and improve product quality across the enterprise by applying advanced analytical tools and techniquesThe analyst will collaborate with subject matter experts (sme’s), project teams, manufacturing excellence leaders, and other leaders within the mills.
The manufacturing data analyst is a key member of the remote analytics team – part of the international paper global manufacturing technology groupThe remote analytics team is a cross-functional team focused on data, advanced analytics, and improving company cost-competiveness thru non-capital opportunitiesThe successful analyst will work from the advanced analytics center, located in atlanta’s technology squareThis position offers “hybrid” working arrangement – the hybrid-working concept includes a mix of working from a home or from the atlanta tech square officeTherefore, the home office will need to be within a typical commuting distance to the atlanta tech square office.
Another key role for a manufacturing data analyst is to continuously improve the remote troubleshooting and process optimization capabilities of international papers global manufacturing technology smes by evaluating, identifying, and then proliferating the use of new analytical tools and related emerging technologies.
Key accountabilities:
Configure, implement, and operationalize advanced analytics tools for industrial manufacturing processesSuch tools include, for example, aveva osisoft pi vision & pi asset framework, braincube, matlab, minitab, salford tree-net, and simca multivariate analytics.
Integration of data from various sources such as pi historian, ge plant applications (proficy) database, and sap.
Collaborate with a variety of internal stakeholders including mill process engineers, manufacturing excellence managers, business unit managers, area process managers, and technology subject matter experts (smes) to understand the context and the business need to maintain the quality of our products, improve the reliability of our plants, improve productivity, and lower production costs.
Build pro-active and constructive relationships with manufacturing sites and with technology subject matter experts (smes)Excellence in customer service is expected.
Model the manufacturing process using advanced statistical methods to minimize manufacturing cost via cost modeling of goods, people, and equipment (continuous improvement analytics)
Continual learning on the technical and organizational aspects of the role are expected.
Develop as a technical subject matter expert in manufacturing data analytics.
Knowledge and experience:
A manufacturing data analyst is a fully qualified practitioner in the area of data science and analyticsThe individual has experience analyzing complex industrial processes, and demonstrated positive resultsHe/she will provide basic and fundamental support in the area of data science and analyticsHe/she can provide facility or project support in area of expertise, but does not need to be generally recognized as a subject matter expert within the organizationRecommendations beyond basics will generally be reviewed by a higher-level sme prior to finalization.
Bachelor’s degree in engineering, computer science, data science or other related quantitative fields.
Prior working knowledge and experience within continuous manufacturing operations such as pulp & paper, power/utilities, chemicals, or refineries are preferred.
The candidate should possess at least 3-5 years of relevant work experience with demonstrated results.
The candidate must have experience using one or more advanced analytics / statistical tools, such as r, python, braincube, matlab, minitab, salford tree-net, or simca multivariate analysis.
The candidate must demonstrate action oriented with strong problem solving and collaboration skills with experience working in a matrix environment
The candidate must demonstrate a passion for continual learning and acceptance of working within a highly innovative, less-structured, environment where self-directed research and prototyping may be required.
Organizational agility and interpersonal skills are essential to be successful as a manufacturing data analyst.
Strong interpersonal and verbal/written communication skills
Differentiators:
Operations and/or engineering experience in pulp & paper manufacturing
Lean six sigma training with a green or black belt certification.
Functional expertise with power bi, pi asset framework, braincube, or simca
Competencies (competitive edge profile):
Creativity
Informing
Organizational agility
Personal learning
Presentation skills
Dealing with ambiguity
Technical learning
Customer focus
Interpersonal savvy
Drive for results
Travel expectations:
Developing relationships with staff at our plant sites will enable the manufacturing data analyst to become an integrated member of the mill manufacturing excellence teamTherefore, travel to sites will be required periodicallyTravel is estimated to be approx25-30% on average with potentially higher travel (40-50%) during the onboarding, training and as required for business reasons.
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International paper is an equal opportunity/affirmative action employerAll qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.
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