Description

The Data Governance Office (DGO) at Humana is seeking an AI and Machine Learning Data Security engineer to support the appropriate and secure use of information assets. DGO coordinates the synthetic data capability for the enterprise that creates widely usable and anonymized data sets by mathematically modeling production data and generating replicas of that data that retain the rich relationships between the data components without compromising individuals’ privacy. The synthetic data capability requires application of generative neural network methodologies supported by considerable amounts of compute, memory, and storage resources within a cloud platform to meet the dynamic demand of the multivariate regression processes. Humana is seeking a Data Science Engineer with AI and Machine Learning experience (particularly in Azure) to operate these processes and to do so with data security disciplines to protect the highly sensitive data required for modeling while in that process.

Responsibilities

Responsibilities

The successful candidate will work within the Machine Learning environment at Humana and with that team to perform activities in support of and related to the build out, maintenance, and enhancement of the Synthetic Data resources. This is a challenging environment that must innovate while respecting the rigors, policies, and constraints of a corporate analytical facility. The Machine Learning team operates in an open environment that encourages sharing of ideas, code, feedback, and documentation of their work.
Tooling includes:

• Python, SQL, Bash, PowerScript, Scala
• SQL Server, Hadoop, PySpark, Kafka, Databricks
• RedHat Enterprise Linux, Windows, Docker, Azure Kubernetes Services
• Git, Azure DevOps, Gira, Confluent

Job Description

• Design, build out, maintain, monitor, and enhance the Synthetic Data environment in Azure
• Interface with Data Scientists, Business Users, and Developers to support their synthetic data requests
• Interface with the synthetic data engine vendor(s) to maintain and enhance the operation of their engine in the Azure platform
• Research and develop enhancements to the pre-processing of data sets for introduction to the synthetic data engine
• Periodically research and present emerging synthetic data innovations from the field to the Data Science community
• Mentor and train Data Scientists and Engineers within Humana’s analytics community to operate synthetic data capabilities

Role Essentials

• BS in Computer Science, Data Science or related field
• 5 or more years of experience designing, developing, and testing software applications and infrastructure
• 3 or more years of machine learning experience
• Experience writing maintainable, testable, production-ready, and documented Python code
• Experience in big data platforms (Hadoop, Spark, Hive, etc. . .) and big data formats (Parquet, Avro, etc. . .)
• Experience with secure development and security features required by cloud infrastructures

Preferred Qualifications

• Terraform deployment of Azure infrastructure configurations
• Experience with deep learning libraries and frameworks (TensorFlow, PyTorch, Keras, etc. . .)
• Master’s Degree in Computer Science, Data Science or related field