Sr. Data Scientist - Telecommute

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

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 is improving the lives of millions. Here, innovation is not about another gadget; it is about making health care data available wherever and whenever people need it, safely and reliably. There is no room for error. If you are looking for a better place to use your passion and your desire to drive change, this is the place to be. It's an opportunity to do your life's best work.(sm)

Optum Enterprise Issue Management is looking for a Sr Data Scientist who will be working with big data across multiple healthcare platforms. This role will be responsible for modeling complex business problems, uncovering data anomalies, discovering business insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques. This individual will need to have a natural desire to go beneath the surface of a problem to ask the right (business) questions, and produce answers in support by digging into large data sources and applying statistical rigor. The ideal candidate will have a knack for thinking “Big Picture” as well as enjoy digging into the details, applying 3 key elements to challenging healthcare problems: Analytical Rigor, Creativity and Business Focus.

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

Primary Responsibilities:

• Analyze complex consumer and case data (e.g. relational databases, star schema’s, etc.) and turn into actionable insights in support of the long and short term goals of the company 
• Integrating and preparing large, varied datasets, both internal member behaviors as well as exogenous data sources, to get a holistic understanding of member preferences and behaviors
• Build predictive and analytical models by using techniques such as logistic regression, OLS regression, k-means segmentation, PCA, decision trees
• Produce meaningful recommendations for influencing member engagement and outreach strategies by using data mining, statistical analysis and predictive modeling 
• Dig beneath the surface of a problem to ascertain the “Why” in the backend data, uncover the true reasons data patterns and skews may be showing up, and convert those findings into clearly understandable, data-backed recommendations, to influence future member engagement strategies
• Uncovering data anomalies, discovering business insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques
• Distil patterns in data, many times dirty data that doesn’t make sense. Ability to spot dirty data and think out of the box about how to accommodate in order to produce trustworthy results given these constraints
• Develop presentations around insights and tell compelling stories with the data, and deliver to constituents at all levels: strategic, tactical, operational, and across functions: marketing, operations, finance, etc. 
• Communicate and present findings, orally and visually in a way that can be easily understood by business counterparts
• Be highly motivated and independent self-starter

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.

To be considered for this position, applicants need to meet the qualifications listed in this posting.

Required Qualifications:

• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science or Actuarial Science or equivalent work experience
• 3+ years of experience in advanced SQL working with relational data in large enterprise environments with large datasets (e.g. 1+billion records) 
• 3+ years of experience with data extraction/manipulation/transformation in environments such as SQL server, Netezza, Teradata, or Oracle 
• 3+ years of experience working with statistics to perform analyses, data modeling and predictive behavioral modeling
• 3+ years of experience in one of the following languages: R, Python, SAS, Spark or other programming languages
• 3+ years of experience combining numerous exogenous data sources (e.g. demographics/psychographics/SDoH) with consumer transactional and behavioral attributes to support advanced modeling efforts

Preferred Qualifications:

• Master’s degree in a quantitative/business field 
• 3+ years of experience developing compelling presentations around insights to be delivered to leaders across the organization and external customers
• Experience with Microsoft Azure or Amazon AWS 
• Experience with experimental design (design of experiments) 
• Experience with applications such as Jupyter Notebooks, Spark 
• Experience with text mining/text analytics
• Highly evolved problem-solving skills and adept at understanding and resolving unstructured problems
• Knowledge of healthcare administrative data (medical claims, enrollment, provider data) 
• Solid knowledge of extracting and developing key consumer insights within a population, distilling insights, and presenting to business leadership