Senior Manager, Engineering – Analytics
- Irvine, CA
This is a great opportunity to establish a data driven culture by partnering with manufacturing, operations, quality and supply chain to enable insight to be gained through analyzing company data.
Essential job functions include:
- Identify new and innovative tools to improve overall analytics capabilities.
- Collaborate with stakeholders (e.g., BUs, Functions and Regions) to understand business challenges, problems and opportunities with significant financial impact to the company. Design, develop and implement solutions, both technical (e.g., Metrics Dashboards, Meta-data additions to enhance reporting and analytics) and non-technical (e.g., ECR process changes, simplified workflow changes). Guide cross-functional teams to resolve issues identified by data analysis and provide recommendations on changes to policies and business processes. Lead the identification of opportunities for leveraging company data to drive business solutions in partnership with stakeholders throughout the organization.
- Perform complex data analysis, develop data driven insights and root-causes for inefficiencies and ineffectiveness of processes, and identify opportunities to improve training, processes, systems and product data quality. Develop innovative solution alternatives to resolve issues, influence and create buy-in with key stakeholders while exercising wide latitude in determining objectives and approaches to critical assignments. Establish predictive modeling framework to increase and optimize production plant and supply chain capabilities. Develop process and tools to expand, monitor, and analyze model performance and data accuracy.
- Provide technical expertise and lead high-level strategic problem-solving sessions with cross-functional teams and stakeholders.
- Lead a significant or multiple process improvement activities including identifying and evaluating course correction/alignment opportunities.
- Perform other duties and responsibilities as assigned.
- Bachelor's degree in Engineering or Science with 12 years of experience in engineering and business intelligence.
- Preferred degree in Statistics, Math, Computer Science or related quantitative field.
- Certification in related discipline preferred (e.g., APICs).
- Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
- Experience working with and creating data architectures.
- Experience working in a medical device and/or regulated industry preferred.
- Excellent documentation, communication (e.g., written and verbal) and interpersonal relationship skills including consultative and relationship management skills.
- Advanced problem-solving skills with an emphasis on product development
- Extensive knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Extensive understanding and knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience querying databases and using statistical computer languages: R, Python, SQL, etc.
- Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, AWS Sagemaker, etc.
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
- Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
E dwards is an Equal Opportunity/Affirmative Action employer including protected Veterans and individuals with disabilities.
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