Reliability Engineer (Data science)
Infotree Global Solutions - thousand oaks, CA
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DATA SCIENTIST Development Supply Chain (DSC) within Manufacturing and Clinical Supply is accountable for the end-to-end delivery of Client's clinical products, including planning, procurement, scheduling & capacity management, warehousing, and worldwide distribution. Additionally, DSC teams are accountable for product set up, business process management and technology solutions to configure new products into the company's clinical supply chain. As an integral part of Client's Process Development organization, DSC provides an innovation ecosystem for supply chain professionals. DSC supports differentiating, multi-modality manufacturing and enables the set up and ongoing support of innovative and biosimilar products in our clinical trials. DSC is seeking an Associate Data Scientist who would be focusing on the integration of complex data sources, performing data analytics on supply chain processes, and developing various visualizations and dashboards! This role will be actively collaborating with a wide range of business leaders and design and implement sophisticated analytical models. Responsibilities will include, but are not limited to: Leverage large datasets to conduct end-to end supply chain analytics that include data gathering and requirements specifications, processing, analytics, and presentations Understand and capture businessfunctional requirements, Interact cross-functionally with a wide variety of people and teams. Synthesize input into prioritized feature list and build User Stories (requirements) for each feature Define and create automated interactive dashboards and tools that are turning data into business insights Document data relations, data flows and business logics behind the supply chain digitalization projects Partner with IS and Data Engineers to ensure that the models feeding the dashboards are robust, functional, and relevant to business needs Ensures delivery of efficient, agile, integrated business and system processes.Qualifications: Experience in a data science, data analyst, business analytics, business intelligence or comparable role Expertise using SQL to write complex queries across large volumes of data Proficiency in programming with Python, or R Tableau developmentvisualization experience including designing and developing reports and dashboards Ability to bridge functions, particularly technical and non-technical worlds Ability to communicate and provide meaningful business insights from data Strong verbalwritten communication skills with attention to details and organization Shown success on delivering results on multiple projects in an agile and fast-paced environmentDescription (What the person will do):Responsible for developing and deploying data-driven tools for asset reliability monitoring for MCS. This is a unique opportunity for Client staff to learn the diverse MCS operations Drug Substance, Drug Product, and Warehouse. Interact with various MCS Fac & Eng SMEs to develop knowledge on KPIs for equipment and advance existing framework of system monitoring analytics. The outcome of this effort will be to build dynamic platforms and data architecture that can aggregate reliability performance of all MCS assets, while providing ability to assess Asset Hierarchy at the system-level down to the component-level. In this role, the staff will be reporting into MCS Reliability Principal Engineer for guidance as well as interact with other F&E plant leaders for client feedback and support.Other key learnings for staff in this role are applications of reliability centered maintenance strategies, predictive maintenance techniques, and good engineering practices, advanced data analytics, and project management capabilities for Reliability Engineering.Responsibilities:• Regularly apply theories and principles from Data Analysis to develop and deploy asset performance monitoring tools.• Developing, programming, improving, automating, and deploying reliability models• Facilitate reliability centered maintenance assessments, collaborate with SMEs to apply six sigma methodologies for improving maintenance strategies, and implementation• Train, perform, and develop reliability tools and procedures (OEE, RCM, FMEA, RCA, reliability models, statistical analysis, FRACAS. etc.)• Contribute to Reliability Engineering strategic planning and continuous improvement opportunities• Create reliability documents, business process documents, schedules, and reports• Collaborate closely with Maintenance, Engineering, Manufacturing to understand and respond to the Voice of the CustomerPreferred Qualifications• Experience with variety of data analysis and modeling methods• Proficient in SpotfireTableau, SQL, Python, R as well as ability to develop advanced visualizations via R-shiny, Dash, or JavaScript technologies• Strong statistics and programming background with proven experience delivering on data analytics• Strong verbal and written communication skillsDesired Skills:Engineering DegreeManufacturing and Operations experienceLean six sigma experienceReliability knowledge is not required but preferredExperience in Facilities & Engineering, Utilities is not required but preferredBasic Qualifications Doctoral degree OR Master degree & 1+ years of directly related experience OR Bachelor degree in Industrial Engineering Supply Chain Business Analytics Computer Sciences OR Life Sciences AND 3+ years of directly related experienceTop 3 Must Have Skill Sets: • Regularly apply theories and principles from Data Science to develop and deploy asset performance monitoring tools.• Facilitate reliability centered maintenance assessments, Implementation of PdMCBM technologies, collaborate with SMEs to apply six sigma methodologies for improving maintenance strategies, and implementation• Train, perform, and develop reliability tools and procedures (RCM, FMEA, RCA, reliability models, statistical analysis, etc.)
Created: 2024-10-07