Director Data Science – Telecommute

Key Skills

Java Programming, Python Programming, SQL, TensorFlow, Apache Hive, MapReduce, Apache Pig, R Programming, SPARK Programming

Job Description

Combine two of the fastest-growing fields on the planet with a culture of performance, collaboration and opportunity and this is what you get. Leading edge technology in an industry that's improving the lives of millions. Here, innovation isn't about another gadget, it's about making health care data available wherever and whenever people need it, safely and reliably. There's no room for error. Join us and start doing your life's best work.(sm) 

The Payment Integrity Decision Intelligence group within Optum Insight is expanding. We are looking for experienced Data Scientists to join this growing team. This individual will be responsible on the development and delivery of large and complex predictive modeling projects for healthcare Payment Integrity processes. Director Data Science – Non-Clinical develops innovative and effective approaches to solve client's analytics problems and communicates results and methodologies. Principal Data Scientist also provides directions and guidelines to Data Scientists to discover business insights, identifies opportunities, and provides solutions and recommendations to solve business problems through the use of statistical, algorithmic, data mining and visualization techniques. In addition to advanced analytic skills, Principal Data Scientist is also proficient at integrating and preparing large, varied datasets, architecting specialized database and computing environments, and communicating results.

You’ll enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges.

Primary Responsibilities:

• Build, mentor, and lead a team of data scientists
• Support the growth and development of our Commercial Payment Integrity Suite of products
• Work alongside other data scientists, engineers, product team and project managers to design and implement models and experiments from end to end, including data ingestion and preparation, feature engineering, analysis and modeling, model deployment, performance tracking and documentation
• Participate in meetings with business stakeholders, data experts, software/platform engineering, and product teams to scope data science use-cases and convert them into scope of work
• Be a hands-on leader and teach by example by building prototypes using variety of predictive methods while adhering to the ML development cycle (e.g., iterative EDA, prediction specification, feature engineering and model tuning)
• Work independently to research new methodologies, software, and hardware to support commercial payment integrity
• Effectively communicate complex technical results to business partners
• Support and drive analytic efforts around machine learning and innovation
• Work with a great deal of autonomy to find solutions to complex problems

You’ll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

• Master's or PhD degree (ideally in machine learning, computer science, statistics, mathematics, etc.)
• 7+ years of experience with manipulating large datasets
• 7+ years of experience with hands-on modeling 
• 5+ years of experience in R or Python
• 3+ years of experience in managing teams
• Solid analytic programming skills
• Understanding of ensemble modeling, ANN, SVM, Random Forests, or Deep Nets
• Demonstrated ability to grasp analytical concepts, and how analytical solutions can help customers reduce their claim costs
• Proven ability to quickly understand new concepts – all the way down to the theorems – and to come out with original solutions to mathematical issues

Preferred Qualifications:

• Experience with healthcare claims data
• Experience with non-clinical Integrity processes
• Experience with Post-Payment Integrity processes
• Understanding of medical coding, such as ICD, CPT, or DRG 
• Experience with Hadoop (MapReduce, PIG, Hive, Spark), H2O, TensorFlow, or similar tools
• Experience in UI design for automated or user-interactive visualizations, displays or reports based on the models’ outcomes