Data Scientist II – Telecommute

Key Skills

Java Programming, Python Programming, SQL, Azure, Keras software library, NumPy, Pandas, PyTorch, TensorFlow, Scikit-learn, R Programming, MxNet, SPARK Programming

Job Description

Optum is a company that's on the rise. We're expanding in multiple directions, across borders and, most of all, in the way we think. Here, innovation isn't about another gadget, it's about transforming the health care industry. Ready to make a difference? Make yourself at home with us and start doing your life's best work.(sm)

The Advanced Analytics team within OptumRx’s Digital Analytics and Intelligence uses sophisticated algorithms and techniques to resolve some of the hardest problems to improve our customers digital experiences. The team uses a blend of scientific, problem solving, and quantitative skills to develop and deliver groundbreaking methods addressing critical problems in our digital environment. The Advanced Analytics team collaborates across product, design, engineer and IT team through data science, machine learning and AI.

Do you want to be part of a growing data science and data engineering team that is helping to shape the digital experiences for millions of customers? As a Data Scientist II, you will work cross-functionally with data scientists, engineers, analysts, and product managers to design, develop, and deploy state-of-the-art machine learning models that make a meaningful difference to millions of our customers. You will glean actionable insights from Optum’s vast trove of data, translate business problems into predictive models.

This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large scale machine learning, reinforcement learning, enable measurable actions and work closely with product and engineering teams. This position will report directly to the Director of Data Science.

Purpose of Position:

You will have opportunity to work on a portfolio of challenges that could include, but are not limited to:

• Enabling anomaly detection capabilities to identify the change in customer behavior that deviate from a normal digital behavior with potential critical incidents or opportunities
• Modelling multi-channel customer behavior and the member journey to improve member engagement and reduce potential frictions
• Researching and developing cohort analysis and customer churn prediction models to reduce drug attrition and lead to better health outcomes

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

Primary Responsibilities:

• Lead and deliver data science solutions leveraging latest machine learning techniques, including exploratory data analysis, feature engineering and selection, model selection, evaluation and cross validation, deployment and productionalization at scale that drive value to Optum
• Research and apply a range of data science methodologies and machine learning models to complex business problems
• Develop, implement, and maintain tools and algorithms using Python and/or other languages with appropriate libraries and frameworks
• Communicate results as well as their uncertainty and limitations effectively to technical and non-technical stakeholders

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:

• Bachelor’s degree in statistics, mathematics, computer science, engineering, or related discipline
• 1+ years of relevant real-world experience researching, developing, and delivering high impact data driven insights through machine learning 
• Deep understanding of supervised and unsupervised machine learning techniques
• High proficiency in exploratory data analysis, data profiling, and feature engineering on large structured and unstructured datasets
• In depth knowledge and hands-on computer programming in SQL, Python, R, or similar programming language

Preferred Qualifications:

• Master’s degree or PhD in statistics, mathematics, computer science, engineering, or related discipline
• Experience presenting to both technical and non-technical audiences and a history of publications or presentations at conferences
• Deep knowledge of probability, statistics, and machine learning algorithms with the ability to determine when to apply them
• Familiarity with big data platforms (like Spark, Databricks), machine learning frameworks (like TensorFlow, Keras, MXNet or PyTorch) and libraries (like scikit-learn, numpy, pandas, and scikit-learn) with the ability to learn new technologies quickly
• Knowledge of Azure, or similar cloud platforms
• Solid communication skills – ability to succinctly communicate results and tell compelling stories with data to any audience (e.g. presenting findings and deep dives to senior leadership)