The Ideal Candidate

5+ to 7 years of experience
Management Experience Required – No
Minimum Education – Bachelor’s Degree

The Reliability Engineer job position is in the Reliability Services group in the Engineering & Services Department at the Longview site.   Personnel in this job position perform work in a variety of areas including: 

(1) performing reliability studies or reliability modeling on specific plant equipment or larger systems to identify and recommend projects to improve plant reliability and reduce conversion cost

(2) providing reliability and maintenance input to capital project design

(3) providing technical support to operating and maintenance departments to support on-going plant operations

(4) data mining and data analysis to identify projects to improve plant reliability and reduce conversion cost.   Individuals in this role will utilize a broad range of mechanical engineering, reliability engineering, project leadership and problem solving skills to perform the Reliability Engineer job.

Job Responsibilities:

-Support operations and maintenance during on-going plant operations including troubleshooting, equipment repairs, and support during major turnarounds

-Provide input into capital project scope and detailed engineering to insure reliable plant design, production at target rates, and low life cycle costs,

-Perform analysis of production loss and equipment failure data using statistical analysis tools and recommend projects to improve reliability

-Lead, facilitate, or participate in root cause analyses of process upsets and equipment failures to identify corrective actions to prevent recurrence

-Lead, facilitate, or participate in failure modes and effects analyses for specific equipment, plant systems, or entire production units to identify improvement projects to improve reliability and reduce conversion cost.

-Coordinate engineering, repair and construction activities for plant alterations and improvements,

-Lead problem solving teams to identify, design and implement improvements

-Effectively utilize and promote the use of reliability tools such as RCA, Weibull analysis, Reliability Modeling, and other reliability tools

-Coordinate and manage reliability project development, design, and installation

Job Qualifications/Skills:

-Broad range of mechanical engineering skills

-Working knowledge and training in basic reliability engineering tools including root cause analysis, failure modes and effects analysis, reliability modeling, Weibull analysis and other reliability tools.

-Practical statistical analysis

-Strong problem solving/troubleshooting skills

-Good understanding of common equipment preventative and predictive technologies

-Ability to effectively handle a large volume of important or urgent issues in a timely manner

-Ability to effectively self manage a very demanding workload

-Ability to work effectively in a team environment with diverse groups of people

-Very high level of initiative

-Very service oriented and customer focused

-Strong commitment to personnel and process safety

-Good written and oral communication skills

-Good team leadership skills

-Strong problem solving and decision-making skills

-Good judgment

-Good planning and organizing skills

-Capital project engineering experience is desirable

-Project management experience is desirable

-Operations or Maintenance experience is desirable

Bachelor (BS) or Master’s (MS) degree in Mechanical Engineering from an ABET accredited university is required. 

 Three years minimum experience in a reliability engineering related job position in the petrochemical or petroleum refinery industry or similar industry is required.

Location: Indiana 

10+ to 15 years of experience
Management Experience Required – No
Minimum Education – Doctoral

Willingness to Travel – Occasionally

The Data Mining group within Advanced Analytics focuses on developing new models, algorithms, and tools in a wide range of technical and business areas, including many areas of Research & Development, healthcare data from electronic medical records or claims databases, Sales & Marketing, Customer Service/Response, B2B, and more.  This opening is for an experienced researcher in applied mathematics, statistics, informatics or other areas of science with an emphasis on data mining and analysis of data. We are especially interested in persons with expertise in developing models based on findings from data mining efforts and understanding variability and spurious/biased findings (i.e. statistical validity) that may come from data mining projects. Successful candidates are expected to work with multidisciplinary teams to solve challenging problems of importance to drug research, development and commercialization. They will also conduct innovative research, publish and present results in refereed journals and conferences.

The successful candidate will provide statistical/mathematical data mining support in multiple dimensions including:

-                  provides technical leadership and expertise to execute multi-disciplinary or cross functional projects that will influence the Lilly Research Laboratory and the Statistical Science organization;

-                  leads the assessment and introduction of new statistical/mathematical technology and methodology to apply to broader practice;

-                  provides consulting on priority R&D/business projects to define questions/problems of interest, define necessary data sources, and effectively communicate findings to scientific and business partners.

-                  assist with decision-making by effective data mining project plans across Eli Lilly

-                  provide appropriate technical oversight and coaching of a small staff of PhD data mining scientists and statistical programmers.

-                  Work with drug/compound Research Teams and a broad variety of business functions to apply data mining techniques to assist in analysis and decision-making.

-                  Perform research and develop methodologies, especially in data mining and other innovative statistical/mathematical approaches.

-                  Stay current with respect to statistical/mathematical/informatics modeling methodology, to maintain proficiency in applying new and varied methods, and to be competent in justifying methods selected.

-                  Develop approaches or solutions that save time, increase efficiency, facilitate decision-making or otherwise directly impact our drug research or business objectives.

-                  Collaborate with other scientists and drug/compound Team personnel to provide input on study protocol and study design through the use of data mining on past studies or other data sources.

-                  Participate in peer-review work products from other statistical/analytical colleagues, and advise others on technical matters.

-                  Can effectively lead cross-functional or multi-disciplinary groups and use technical expertise to influence business decisions through statistical/mathematical analysis and interpretation.

-                  Collaborate with team/functional colleagues to write reports and communicate results.

-                  Assist with, or be responsible for, communicating study results via manuscripts, or oral presentations in group settings, as well as for communicating one-on-one with key customers and presenting at scientific meetings.

-                  Assist project statisticians in responding to regulatory queries and to interact with regulators as needed.

-                  Have broad understanding about the drug development business to assist in defining data mining projects that may improve efficiency in our business.

-                  Understand disease states in order to enhance the level of customer interaction and collaboration and be seen as a strong scientific contributor.

-                  Perform work in full compliance with assigned curriculum(s) and will be responsible for following applicable corporate, medical, local, and departmental policies, procedures, processes, and training.

-                  Develop, train, educate others in Statistical Sciences and other technical disciplines in research and business on the use of data mining methods and tools.

If interested, please submit your resume to resumes@acquis.com.  Thank you!