Senior Data Scientist - ECOM Clinical Analytics amp Trend Remote Nationwide

Profile

Description

Humana's Clinical Trend and Analytics Team is seeking a Senior Data Scientist.

The Clinical Trend and Analytics team uses advanced scientific techniques, forecasting, and machine learning to predict financial and clinical outcomes in order to guide investments that improve health outcomes and reduce costs. In this exciting start-up environment, you'll have the opportunity to develop data science processes from the ground up and work directly with decision-making executives to shape the future of Humana's most important strategic initiatives.

We think big and relentlessly innovate to redefine the future of healthcare with data science.

The Senior Data Scientist uses mathematics, statistics, machine learning, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Senior Data Scientists' work assignments involve moderately complex to complex issues where the analysis of situations and data requires an in-depth evaluation of variable factors. The Senior Data Scientist uses machine learning and artificial intelligence to develop sophisticated models based on large structured and unstructured data set, exercises considerable latitude in determining objectives and approaches to assignments.

Responsibilities

As a Senior Data Scientist, you will:

Use techniques from supervised and unsupervised machine learning, statistical analysis, or predictive modeling to deliver business insights and analytics solutions

Work directly with aligned business partners in requirements definition, project scoping, timeline management, results documentation, and maintain effective and professional working relationship

Create reusable implementations of statistical tests and machine learning models using the available technologies in the ecosystem

Build 'smart' systems that learn from health intervention outcomes over time

Generate new product requirements for the engineering group to enhance the analytics capabilities of the database

Use machine learning techniques to assess outcomes of interventions and clinical programs

Collaborate with multiple cross-functional teams to identify operational barriers and issues, and facilitate their resolution

Required Qualifications

Academic training in a quantitative discipline such as Economics, Epidemiology, Clinical Informatics, Math, Statistics, Computer Science, Engineering, Data Analytics or related field

Professional experience leveraging structured and/or unstructured healthcare data

Experience in using mathematics, statistics, modeling, experimental study design, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions

Experience using supervised and unsupervised machine learning techniques such as regression, random forest, xgboost, clustering and/or causal inference techniques such as hierarchical modeling, fixed effect/random effect models, propensity score matching, etc

Experience with Spark and building end-to-end modeling pipeline using PySpark, Spark ML, Scala, or similar tools

Experience working with and analyzing various types of data using Python, R, SAS, or similar software

History of solving problems, creating solutions and driving change within a team

Demonstrated strategic and analytical thinking

Clear and concise oral and written communication skills, with a proven ability to translate complex methodologies and analytical results to higher-level business insights and key takeaways

Ability to make decisions on moderately complex to complex issues regarding technical approach for project components

Flexible, dynamic personality who is able to work independently in a start-up environment Preferred Qualifications

Strong business acumen, including a deep understanding of healthcare payer economics

Master's or PhD Degree in a quantitative discipline such as Economics, Epidemiology, Clinical Informatics, and/or related fields.

Clinical degrees also preferred Demonstrated familiarity with clinical concepts related to a broad range of clinical conditions and disease states, utilization management, claims Episode Treatment Groupers

Experience with causal inference methodologies such as hierarchical modeling, fixed effect/random effect models, propensity score matching, etc

Experience with advanced machine learning algorithms such as neural networks, deep learning, recommender system, isolation forest, network analysis, and/or causal inference techniques such as causal forests, regression discontinuity analysis, instrumental variable analysis, path analysis etc.

5 years' technical experience

Experience with EMR data Additional Information Healthcare is rapidly changing, and our members are living longer, often with more chronic conditions. Consumers expect more personalized and holistic experiences from their health partners. Humana's Enterprise Clinical Operating Model (ECOM), is a multi-year strategy with the goal of improving member experiences and health outcomes through better integrating Humana's processes, technology and clinical capabilities. The person occupying this role will be instrumental in executing on the vision of ECOM in partnership with leaders and teams across Humana.

Scheduled Weekly Hours

40

Company info

Humana Inc.
Website : http://www.humana.com