Miami - Senior Biomedical Data Scientist

Level of the Role: Senior Biomedical Data Scientist

Years of experience: 5+ years

Language: English B2+

Client location: Miami, Florida

Place of work: UHealth Medical Campus

About the role:

The Senior Biomedical Data Scientist will lead the development of cutting-edge bioinformatics pipelines and tools, enabling large-scale data analysis and visualization for biomedical research. This role requires deep expertise in NGS data analysis, cloud computing, and data integration for healthcare research platforms. Working in a multidisciplinary team, you will directly impact the research efforts of the Sylvester Comprehensive Cancer Center by creating scalable, production-ready solutions.

In this role, you will:

· Develop :

o Build and maintain production pipelines for processing and analyzing biomedical and clinical data (e.g., RNA-seq, WGS/WES, ATAC-seq).

o Develop computational tools for exploring large-scale multi-omic datasets.

· Collaborate :

o Work closely with research scientists, data engineers, and full-stack developers to ensure integration with Sylvester’s internal end-user data analytics platform.

o Assist in integrating publicly available datasets with internal research workflows.

· Optimize :

o Design and implement scalable data management and storage solutions using cloud environments (e.g., Azure).

o Create workflows to enhance research activities, including real-time data analysis and visualization.

· Document:

o Write standard operating procedures and maintain technical documentation for developed solutions and pipelines.

Requirements

We are looking for someone who has:

· 5+ years in bioinformatics, computational biology, or related fields.

· Advanced knowledge in NGS data analysis and bioinformatics tools (e.g., BWA, GATK, STAR, Picard).

· Expertise in R or Python and Unix (bash) scripting.

· Proficiency with workflow management systems (e.g., Cromwell) and pipeline workflow languages (e.g., WDL).

Strong experience with Cloud Computing environments (e.g., Azure).

Additional Skills (Optional – It’s a plus):

· Familiarity with High Performance Computing.

· Knowledge of machine learning frameworks (e.g., TensorFlow, Scikit-learn) and deploying ML models.

· Experience with container technologies (e.g., Docker).

· Familiarity with relational (PostgreSQL) and/or NoSQL databases (MongoDB).

· Experience integrating with EMR systems (EPIC preferred).

Skillset:

Skill

Mandatory

Optional – it’s a plus

NGS Data Analysis (e.g., RNA-seq)

x

Workflow Management System

x