Job Description
An employer in Oceanside, CA is looking for a Data Engineer II to join their team. They will work in a hybrid capacity and will be required to come onsite 2 to 3 times per week.
Job Overview:
Data Science plays a key role in transforming vast amounts of structured and unstructured data into insights, building predictive analytics and machine learning (ML) models for complex business problems that enable the organization in data-driven decision making. This is why we have recently created an analytics chapter within our Data and Digital Organization, to take advantage of analytics across our digital products. Within the analytics chapter, you will work as an innovator, inventor, investigator, partner, engineer, firefighter'' and, of course, as a scientist. You will be hands-on with implementation data and analytics pipelines, and build new business solutions and challenge the status quo. In addition, you will be key to actively build new Data Products published in our Data Mesh and work closely with Subject matter experts within the manufacturing, quality and development organizations of PT to deliver fit-for-purpose-analytics.
Responsibilities:
Be part of a cross-functional use case team to address high-pressing business problems and become familiar with our product-related data, manufacturing processes and systems
Undertake appropriate preprocessing of structured and unstructured data with additional support of Data Engineers and evolve and build new Data Products
Analyze small to large amounts of static and real-time data to discover trends and patterns, and to implement analysis pipelines
Build, validate, and deploy predictive models and Machine-Learning (ML) algorithms to predict manufacturing related issues of the products
Maintain ML model lifecycle to ensure it fits for the intended use over time.
Required Skills & Experience
o Education and experience:
Masters with 2 years relevant work experience, or PhD degree in Software
Engineering, Statistics, Data Science, Bioinformatics or a related field.
o Skills:
Advanced knowledge of programming languages (Python, R) and ability to implement
pipelines
Proficiency in developing ETL data pipelines and using cloud computing to run
pipelines and ML models (GCP/AWS)
Extensive knowledge of ML frameworks, data structures, modeling, and software
architecture.
Rich experience in ML model validation and lifecycle management.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.