Data Science Solutions Consultant at Elevance Grand Prairie, Texas

Data Science Solutions Consultant Senior

Ideal candidates will be able to report to our Pulse Point location at 2505 N Hwy 360, Grand Prairie, TX 75050. This role requires associates to be in-office 1 - 2 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. Work Hours: Monday to Friday, 8:00 am to 5:00 pm

The Data Science Solutions Consultant Senior is responsible for engaging in Model Ops life cycle. How You Will Make an Impact:

• Build new Data Ingestion Pipeline.
• Operationalize machine learning (ML) models.
• Deploy the Machine Learning models in Pre-production and Production cycles.
• Monitor Model Performance for any drifts.
• Data Ingestion and Model Ops using Python, Spark, Scala software within Enterprise Data Science and AI organization.
• Engage in on-premises AWS cloud migration activities.
• Enable Model Ops in AWS Cloud environment.
• Perform tasks in Snowflake and create complex SQL's to support Model Ops activities.

Minimum Requirements:

• Bachelor's degree in Computer Science, Computer Engineering, or a related field.
• Five (5) years of experience in Any occupation with experience in predictive analytics and software technologies.

Experience Requirements:

• Five (5) years of experience in any occupation with experience in predictive analytics and software technologies must include:

• Three (3) years of Snowflake and complex SQL experience,or related;
• Software technologies such as Hadoop;
• Experience with deployment techniques within an Agile development methodology;
• Spark;
• Scala;
• Python;
• Big Data with Cloud AWS;
• AWS technologies EC2, EMR, Lambda, Cloud Watch and Bootstrap;
• API;
• Airflow Dag;
• Kubernetes;
• and CAAS (Container as Services).