Senior Data Scientist

Vizient•Irving, TX

17d•$141,773 - $179,000•Onsite

About The Position

When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. DUTIES: Develop data science solutions and insights across multiple projects, combining an understanding of healthcare concepts with advanced mathematics to maximize the value of data for company’s members. Serve as a subject matter expert and work on cross-domain data science design related to machine learning, statistical inference, natural language processing, risk adjustment, data standardization and mapping, and other key data enrichments. Specific duties will include the following: 1) Conduct exploratory data analysis from complex, disparate data sources to recognize patterns and support large scale delivery of key data insights through rigorous and transparent methods; 2) Operationalize data modeling, exploratory data analysis, inferential statistics machine learning model development, project deployment, and visualization based on specified project goals or design objectives; 3) Utilize structured query languages (SQL/Spark) and statistical programming languages (Python/SAS/R) to construct comprehensive data processing software solutions which clean, evaluate, and analyze a variety of data sets; 4) Leverage machine learning, natural language processing, or other statistical approaches to create, trouble shoot, and implement single platform solutions; 5) Apply technical knowledge in order to optimize program processing times and data representations and apply healthcare domain knowledge in order to understand how data represents real world situations to mold methods appropriately; 6) Communicate and interweave cross-domain findings from exploratory and predictive data analysis broadly to internal and external leaders; 7) Identify improvement opportunities in reporting and BI tools and collaborate with Products Technology to implement enhancements; and 8) Collaborate with key leaders and business expert to build analytical acumen across all analytic roles and business leaders across multiple projects within specific organizational domain. Uses the following methodologies, tools, and technologies: Inferential statistics (Chi Squared, Z scores, T tests), predictive statistics (AHRIMA, regression), machine learning models (SVM, random forest, neural net, natural language processing), healthcare data standards (ICD-10, LOINC, MSDRGs), statistical inference and experimental design (A/B testing, confidence intervals, power analysis), Python libraries (statsmodels/scikit-learn), core programming tools (R, Python, SAS, SQL, MATLAB, JAVA), and data platforms (Apache Spark, Azure Data Bricks, Hadoop).

Requirements

This position requires a Master’s degree or equivalent in Data Science or a related field and 3 years of experience in a data science/analysis or related occupation. Will accept experience gained before, during or after a Master’s program. In the alternate, employer will accept a Bachelor’s degree or equivalent in Data Science, or a related field, and 5 years of (progressive, post-baccalaureate) experience in a data science/analysis or related occupation.
Must also have 24 months of experience with each of the following: 1) Using inferential statistics (Chi Squared, Z scores, T tests) and predictive statistics (AHRIMA, regression).
2) Leveraging machine learning and natural language processing approaches, including SVM, random forest, neural net, natural language processing.
3) Utilizing structured query languages (SQL/Spark) and statistical programming languages (Python/SAS/R) to construct comprehensive data processing software solutions.
4) Using statistical inference and experimental design (A/B testing, confidence intervals, power analysis) and Python libraries (statsmodels/scikit-learn). Employer will accept experience gained concurrently.
Domestic travel up to 10% of the time per year.

Responsibilities

Conduct exploratory data analysis from complex, disparate data sources to recognize patterns and support large scale delivery of key data insights through rigorous and transparent methods
Operationalize data modeling, exploratory data analysis, inferential statistics machine learning model development, project deployment, and visualization based on specified project goals or design objectives
Utilize structured query languages (SQL/Spark) and statistical programming languages (Python/SAS/R) to construct comprehensive data processing software solutions which clean, evaluate, and analyze a variety of data sets
Leverage machine learning, natural language processing, or other statistical approaches to create, trouble shoot, and implement single platform solutions
Apply technical knowledge in order to optimize program processing times and data representations and apply healthcare domain knowledge in order to understand how data represents real world situations to mold methods appropriately
Communicate and interweave cross-domain findings from exploratory and predictive data analysis broadly to internal and external leaders
Identify improvement opportunities in reporting and BI tools and collaborate with Products Technology to implement enhancements
Collaborate with key leaders and business expert to build analytical acumen across all analytic roles and business leaders across multiple projects within specific organizational domain