NLP Data Science Intern(Python & SQL Expertise) - Data Analytics/Data Science Intern

Department Overview:

Our data science team is committed to leveraging advanced data science techniques to make unstructured data more manageable, supporting critical applications and enhancing quality of care through data-driven solutions. This internship requires a commitment of 4 days per week, allowing interns to gain substantial experience while balancing other responsibilities.

Job Description

Supports data analytics and data science teams. Prepares data for analysis helping with data extraction and organization. Assists the conducting of analyses. Performs related clerical functions.

Job Responsibility

• Supports data analytics and data science teams.
• Prepares data for analysis helping with data extraction and organization.
• Assists the conducting of analyses.
• Performs related clerical functions.
• Operates with direct guidance and work assignments are generally straightforward and of moderate complexity.
• Performs related duties as required. All responsibilities noted here are considered essential functions of the job under the Americans with Disabilities Act. Duties not mentioned here, but considered related are not essential functions.

Job Qualification

• Bachelor's Degree required, or equivalent combination of education and related experience.
• 0-1 years of relevant experience, required.

Preferred Skills:

• Expertise in Python and SQL for data manipulation and analysis.
• Strong background in object-oriented programming.
• Practical experience in Natural Language Processing (NLP).
• Experience with Deep Learning, Pytorch, Huggingface preferred.
  
  

*Additional Salary Detail

The salary range and/or hourly rate listed is a good faith determination of potential base compensation that may be offered to a successful applicant for this position at the time of this job advertisement and may be modified in the future.When determining a team member's base salary and/or rate, several factors may be considered as applicable (e.g., location, specialty, service line, years of relevant experience, education, credentials, negotiated contracts, budget and internal equity).