Data Engineer WFH

Key Skills

Aartificial intelligence, Algorithms, Analytical and Problem solving, AWS, Azure, Azure COSMOS, Data Modeling, Data science techniques, Effective communication skills, Google BigQuery, Machine learning techniques, MLOps tools, Python Programming, Red Hat OpenShift, SQL, Teradata

Job Description

Note: Eligibility for benefits may vary by location.

We are seeking a highly motivated Data Engineer that is ready to enter the world of MLOps. In this role you will work closely with the Data Scientist and data owners to prepare the data sets and build data pipelines needed for machine learning and statistical models from various data source. You will be with us on our journey as we convert our existing on-prem models to Cloud based models.

Job Summary 

We are seeking a highly motivated Data Engineer that is ready to enter the world of MLOps. In this role you will work closely with the Data Scientist and data owners to prepare the data sets and build data pipelines needed for machine learning and statistical models from various data source. You will be with us on our journey as we convert our existing on-prem models to Cloud based models.

Job duties include but not limited to: 

• Work to understand source systems to pull data from and then build out an ETL process to populate a Data Model that can be used to house the training data
• Will need to perform data cleansing and data profiling. 
• Data Gathering and presentation will use combinations of Python, Azure, BigQuery, Cosmos, Openshift and Vertext AI 
• Building and maintaining data pipelines that are optimized for machine learning applications 
• Collaborate with cross-functional teams to ensure successful implementation and deployment of machine learning model
• Continuously monitor and evaluate the performance of machine learning models in production 
• Stay up-to-date with the latest advancements in machine learning and related technologies 
• As needed, document topology, processes, and solution architecture. 
• Assist with the training and enablement of end users, including data scientists, program managers, and data consumers. 
• Utilize benchmarks, metrics, and monitoring to measure and improve services. 
• Assists with other duties as assigned 

Education 

• Bachelor's degree in Computer Science, Mathematics, Statistics or a related field preferred 
• Will consider work experience in lieu of Degree or Bachelors Degree 

Experience 

• 2-5 years of a solid background in SQL and data modeling with large datasets. Preferably in Teradata or SQL Server
• 1-2 years of strong programming skills in Python 
• Familiarity with tools/platforms such as AWS, Azure, Big query, Cosmos, Openshift, Vertext AI 
• Basic understanding of machine learning algorithms and concepts 
• Excellent problem-solving and analytical skills 
• Ability to work independently as well as in a team environment 
• Strong communication and interpersonal skills
• Good track record of presenting findings and analysis to Executives
• Proven ability to work with business owners, technical owners and key stakeholders to gather requirements and work through testing scenarios

Parallon provides full-service revenue cycle management, or total patient account resolution, for HCA Healthcare. Our services include scheduling, registration, insurance verification, hospital billing, revenue integrity, collections, payment compliance, credentialing, health information management, customer service, payroll and physician billing. We also provide full-service revenue cycle management as well as targeted solutions, such as Medicaid Eligibility, for external clients across the country. Parallon has over 17,000 colleagues, and serves close to 1,000 hospitals and 3,000 physician practices, all making an impact on patients, providers and their communities.

HCA Healthcare has been recognized as one of the World’s Most Ethical Companies® by the Ethisphere Institute more than ten times. In recent years, HCA Healthcare spent an estimated $3.7 billion in cost for the delivery of charitable care, uninsured discounts, and other uncompensated expenses.