10126 Enterprise Corporate - Enterprise Advanced Analytics

Full time

Yes

40

Fully Remote
 

Pay Range

$51.05 - $76.60

Major Responsibilities:

• Collaborate with stakeholders and subject matter experts to define and refine data-driven initiatives that enhance healthcare operations and outcomes. 
• Develop a strong understanding of complex, high-volume, and heterogeneous data, ensuring rigorous data development, cleaning, and validation.  
• Apply machine learning and statistical modeling techniques, including regression, classification, clustering, time series forecasting, and ensemble methods.  
• Utilize LLM-based text analytics and NLP techniques to extract insights from unstructured data sources such as clinical notes and reports.  
• Perform exploratory data analysis and build structured analytical workflows using Python, R, and SQL.  
• Communicate findings and methodologies effectively to both technical and non-technical audiences through reports, presentations, and interactive visualizations.  
• Independently manage projects, setting clear objectives, benchmarks, and milestones while balancing iterative development with accountability.  
• Develop well-documented, reusable code on cloud computing platforms to support analytical pipelines.  
• Follow best practices in collaborative software development, including version control (Git) and modular code design.  

Licensure, Registration, and/or Certification Required:

• None

Education Required:

• PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, Biomedical Informatics or a related field, OR a Master’s degree with 2-4 years of applied experience in data science or machine learning. 

Experience Required:

• ​​ Typically requires 2-4 years of experience in solving complex problems in an analytical environment 

Knowledge, Skills & Abilities Required:

• Extensive experience working with large-scale structured and unstructured data, ensuring data quality and interpretability.  
• Proficiency in Python and/or R for advanced data analysis, machine learning, and model deployment, along with strong SQL skills for working with large datasets.  
• Expertise in statistical modeling, machine learning, and AI techniques, including regression, classification, time series forecasting, and ensemble methods, with experience in at least some advanced techniques (e.g., Bayesian inference, causal modeling, deep learning, LLMs, NLP, or knowledge engineering).  
• Demonstrated ability to lead collaborations with stakeholders, define analytics initiatives, and mentor junior team members.  
• Strong critical thinking and problem-solving skills, with an iterative and pragmatic approach to real-world challenges.  
• Proven ability to translate complex data into actionable insights, using storytelling, interactive dashboards, and presentations.  
• Ability to independently manage multiple complex projects, set clear objectives, and drive high-impact initiatives.  
• Experience writing clean, reusable, and well-documented code and working with containerization tools like Docker for model deployment.  

Physical Requirements and Working Conditions:

• Requires extensive amounts of time working at a computer. 
• Work can be performed in an office environment or remotely. 

Preferred Job Requirements

• Experience working with healthcare data (EHR, claims, clinical notes, imaging, operational workflows).  
• Exposure to MLOps principles, including model monitoring, lifecycle management, and CI/CD for ML models.  
• Experience integrating AI/ML models into production environments, such as API-based decision support or real-time analytics.  

No relocation-No Sponsorship or transfer of visa now or in the future.

Disclaimer: Advocate Health does not provide Sponsorship for employment visa status (e.g. H-1B visa status), nor is Advocate Health able to provide extensions of optional practical training (OPT) under STEM-designated degree programs for F-1 students. To be considered for permanent employment with Advocate Health all applicants must be currently authorized to work in the United States on a full-time basis.

Preferred remote locations in IL, WI, NC, GA

Fully Remote Role from these states: AL, AK, AR, AZ, DE, FL, GA, IA, ID, IL, IN, LA, KS, KY, ME, MI, MO, MS, MT, NC, ND, NE, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, WI, WV, WY.

Due to complex requirements, remote work is NOT permitted for short or long periods in: CA, CO, CT, HI, MA, MD, MN, NJ, NY, OR, RI, VT, WA and working Internationally (this includes working while on vacation).

This job description indicates the general nature and level of work expected of the incumbent. It is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the incumbent. Incumbent may be required to perform other related duties.

Our Commitment to You:

Advocate Health offers a comprehensive suite of Total Rewards: benefits and well-being programs, competitive compensation, generous retirement offerings, programs that invest in your career development and so much more – so you can live fully at and away from work, including:

Compensation

• Base compensation listed within the listed pay range based on factors such as qualifications, skills, relevant experience, and/or training

• Premium pay such as shift, on call, and more based on a teammate's job

• Incentive pay for select positions

• Opportunity for annual increases based on performance

Benefits and more

• Paid Time Off programs

• Health and welfare benefits such as medical, dental, vision, life, and Short- and Long-Term Disability

• Flexible Spending Accounts for eligible health care and dependent care expenses

• Family benefits such as adoption assistance and paid parental leave

• Defined contribution retirement plans with employer match and other financial wellness programs

• Educational Assistance Program

Note: Eligibility for programs listed above may depend on your FTE or status (e.g., full-time, part-time, per diem, temporary, etc.); please ask a Recruiter for more information during an interview.