Data Scientist II

Classification Title:

Data Scientist II 

Classification Minimum Requirements:

A Bachelor's Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience; Master's Degree in data science, statistics, bioinformatics, analytics, or similar field and one year of experience; Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field.

Job Description:

The Computational Microscopy Imaging Laboratory (CMI Lab), within the Department of Medicine, is seeking a highly organized and dependable Data Scientist II to support federally funded research initiatives focused on development and enhancement of secure, cloud-based data platforms and analytical systems.
This position supports research-facing applications that enable clinical data analysis, computational imaging workflows, and advanced statistical modeling. The Data Scientist II contributes to both analytical development and platform enhancement, including development of statistical and machine learning methods, support of backend data systems, and collaboration with investigators and technical staff to ensure that analytical tools and applications are scalable, secure, and aligned with research objectives.
This role operates with moderate independence and contributes to technical design decisions, data architecture planning, and implementation of reproducible analytical workflows.
The position reports to Dr. Pinaki Sarder, Principal Investigator.

Essential Functions; 

Data Systems Development and Integration 
- Design, develop, and maintain scalable data pipelines supporting research applications and analytical workflows.
- Contribute to database architecture, query optimization, and secure integration of research datasets.
- Develop and maintain backend services and APIs enabling secure data access and model deployment.
- Ensure compliance with institutional data governance, HIPAA, and sponsor requirements.

Research Application and Platform Enhancement
- Contribute to the development and enhancement of research-facing web applications and analytical dashboards.
- Support front-end and backend integration to ensure system usability, performance, and scalability.
- Participate in feature testing, validation, and documentation of platform components.
- Assist in deployment workflows, including containerization and cloud-based infrastructure support.

Analytical Support and Method Development
- Develop and implement statistical analyses and applied machine learning methods as required to support research objectives.
- Perform data cleaning, transformation, and validation across structured research datasets.
- Evaluate model performance and support reproducible analytical workflows.

Collaboration, Reporting, and Scientific Contribution 
- Work with investigators and technical leads to define system and analytic requirements.
- Contribute to grant reporting, progress documentation, and manuscript preparation.
- Present technical updates during internal meetings and consortium discussions.

Technical Planning and Process Improvement –
- Contribute to workflow standardization, documentation practices, and version control processes.
- Provide input on system improvements to enhance performance, reliability, and maintainability.

Administrative and Coordination Support 
- Assist with preparation of technical materials for meetings, training sessions, or stakeholder demonstrations.
- Support coordination of development timelines and task tracking activities.

Infrastructure and Tool Evaluation 
- Evaluate emerging analytical tools, frameworks, or technologies to support research development needs.
- Assist in testing and recommending improvements to development environments or deployment workflows.

Expected Salary:

$70,000 - $92,500 annually

Required Qualifications:

A Bachelor's Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience; Master's Degree in data science, statistics, bioinformatics, analytics, or similar field and one year of experience; Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field.

Preferred:

Demonstrated experience developing and maintaining data pipelines and backend systems supporting research applications.
Experience with statistical analysis and applied machine learning in research or healthcare-related environments.
Proficiency in Python and associated data science libraries (e.g., pandas, scikit-learn) and experience working with SQL-based databases.
Experience with API development, backend frameworks (e.g., Flask, Django), or cloud-based deployment environments.
Familiarity with secure data handling practices and regulatory environments involving protected or