Data Scientist

Job Summary

The Data Scientist is responsible for applying advanced analytics statistical modeling and machine learning techniques to solve business problems and improve outcomes across Humana. This role partners with business product engineering and architecture teams to develop data-driven solutions that support enterprise strategies while aligning to Humanas data security governance and architecture standards.

Key Responsibilities

Analyze large complex datasets to identify trends risks opportunities and actionable insights.
Build validate and deploy statistical predictive and machine learning models.
Translate business problems into analytical approaches and measurable outcomes.
Partner with Data Engineers Application Architects Product Managers and business stakeholders to design scalable analytics solutions.
Develop experiments forecasting models segmentation methods and decision-support tools.
Communicate findings through dashboards visualizations presentations and technical documentation.
Support model monitoring performance evaluation and continuous improvement.
Ensure solutions align with enterprise data architecture reference standards and approved technology patterns.
Follow Humana policies for information protection least-privilege access secure storage and confidential data handling.
Contribute to reusable analytics assets standards and best practices across teams.

Required Qualifications

Bachelors degree in Data Science Statistics Computer Science Mathematics Engineering Economics or related field.
Experience in data science advanced analytics or machine learning.
Strong knowledge of:
Python and/or R
SQL
Statistics and hypothesis testing
Machine learning methods
Data wrangling and feature engineering
Experience working with cloud or enterprise analytics platforms.
Ability to communicate technical results to non-technical stakeholders.
Experience working with cross-functional teams in a regulated or enterprise environment.

Preferred Qualifications

Masters or PhD in a quantitative field.
Experience with Databricks Spark or large-scale distributed data platforms.
Experience in healthcare payer claims member provider or clinical analytics.
Familiarity with MLOps model governance and production model deployment.
Experience with BI and visualization tools such as Power BI or Tableau.
Understanding of data architecture cataloging and enterprise data standards.

Technical Skills

Programming: Python R SQL
Data Platforms: Databricks Spark cloud data platforms
Modeling: regression classification clustering time series NLP experimentation
Visualization: dashboards storytelling exploratory analysis
Data Management: data dictionaries data models schema awareness governed datasets

Soft Skills

Analytical thinking
Problem solving
Stakeholder communication
Collaboration
Documentation discipline
Business acumen

Compliance and Security Expectations

Handle data in accordance with Humana information protection and acceptable use requirements.
Use least-privilege access and approved enterprise tools only.
Protect confidential and restricted information in analysis storage sharing and reporting.
Follow approved enterprise architecture data-sharing and platform standards.