Lead Cognitive/Machine Learning Professional - MLP

You will have the opportunity to work on challenging Machine Learning and AI projects with the goal to improve the everyday life of our members. As Lead, you may direct a small team of engineers. You will collaborate with data scientist, analyst, business and IT teams to design, implement, and deploy Machine Learning and AI services using Python, PySpark, Azure services, Databricks, Terraform, and other open-source software. You will be expected to lead by example, to develop plans, designs, code, and documentation, and to perform code reviews, testing, and debugging. You will embrace and enforce best practices in our data science community with automated, repeatable data pipelines.

Some examples of how we add capabilities to Humana's Machine Learning Platform include:

Creating templates for data scientists, embracing leading-edge modeling techniques

Establishing a Feature Store with tens of thousands of features available to use in predictive models

Defining monitoring, auditing, data lineage, and dependency tracking for data pipelines to improve quality

Integrating ethical AI bias monitoring and drift analysis into modelling processing

Standardizing the definitions of clinical, financial, and actuarial features for use across the business

Engineering Philosophy

Building safe, secure data science applications in the cloud is not easy or trivial. It requires solid design, software development and social skills. Knowing this we work as a team to break apart the challenges inherent to our domain and work together to develop the best solution possible. To do this our team operates in an open environment where everybody is promoted to share their code and ideas, provide feedback on code/processes and document their work.

Some of the tools we use

Python, PySpark, Azure Databricks

Azure Data Factory, Azure DevOps, Azure Kubernetes Service, CosmosDB, AppInsights, Kafka, Pulsar

Terraform

Open-source ML software, like SciKit Learn, SparkML, TensorFlow, Horovod, Petastorm

Responsibilities

Build and deploy ML models on Azure, using best practices in security, and Azure services

Understand best practices for effective predictive models, including cluster management and algorithms, and evangelize with Humana Data Scientists

Thrive in a fast-paced agile environment, closely interacting with business analysts, software engineers, machine learning scientists, data engineers, and data scientists

Mentor junior team members, to help grow and mature the overall skillset of the team

BS in Computer Science or related field

3 years of experience working on cloud platforms

5 years of experience with Machine Learning and AI

5 years of software development experience, with significant Python experience

Solid knowledge of data structures and algorithms

Ability to learn new technologies and comprehend unfamiliar data domains and business processes quickly

Role Desirables

Open-source contributions and portfolio of shipped code at GitHub

Familiar with healthcare applications, terminologies, and data

Passion projects with ML/AI/NLP, for example Kaggle competitions and Hackathons