Sr Manager Data Science - 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)

Positions in this function produce innovative solutions driven by exploratory data analysis from unstructured, diverse datasets typically measured in gigabytes or larger. Applies knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. Uses a flexible, analytical approach to design, develop, and evaluate predictive and prescriptive models and advanced algorithms that lead to optimal value extraction from the data. Works with analytics and statistical software such as SQL, R, Python, Hadoop and others to perform analysis and interpret data. This function is not intended for employees performing the following work: less complex analysis on small data sets; rules-based algorithmic or descriptive analytics; development of big data infrastructure.

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

Primary Responsibilities:

• Analyze complex member 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
• Responsible for 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
• Highly motivated and independent self-starter
• Manages and is accountable for professional employees and/or supervisors
• Impact of work is most often at the local level

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:

• Undergraduate degree or equivalent experience
• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science or Actuarial Science
• 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 is required
• 3+ years of experience in one of the following languages: R, Python, SAS
• 3+ years of experience developing compelling presentations around insights to be delivered to leaders across the organization and external customers
• 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
• 3+ years of statistical modeling experience using analytical algorithms such as Logistic Regression, OLS regression, etc.

Preferred Qualifications:

• Experience leading a team of Analysts, engineers and data scientists
• Excellent written and communication skills