[Hiring] Data Scientist III @Moffitt Cancer Center

Role Description

The Data Scientist III (DS) will work directly with key stakeholders throughout Moffitt to document data-related needs and identify novel approaches, including advanced data science and analytics techniques, for addressing those needs. The DS will incorporate these novel approaches into the larger Health Data Services and Digital Innovation strategies. The DS will liaise directly with both clinical and research faculty whose work is focused on genomics, radiomics, immuno-oncology, evolutionary therapy, patient-reported outcomes, and other areas to ensure Moffitt’s analytics methods are best positioned to accelerate discovery using Moffitt’s vast data assets.

• Optimizing the use of Moffitt’s data assets requires careful considerations of data formatting, lineage, quality, linkages, and visualizations.
• As Moffitt continues to incorporate new data types into its cloud-based analytics platform, modern strategies for data provenance, ingestion, linkage, and dissemination will become critical.
• Innovative data types include, but are not limited to:
  • Medical record text
  • Radiology and pathology images
  • Molecular data
  • Patient-generated data (wearables)
• The DS will implement Moffitt’s data and analytics strategy through:
  • Creation of predictive models and algorithms
  • Manipulation of datasets to identify trends and extract meaningful knowledge
  • Development of data mining solutions using natural language processing and machine learning
• Such work will have an immediate and high impact on clinical use cases, such as tumor boards, and on cutting-edge research, such as automation of tumor segmentation.

Qualifications

• PhD or Master's degree in Biostatistics, Epidemiology, Statistics, Data Science, or a related quantitative discipline.
• Advanced expertise in statistical modeling, survival analysis, predictive analytics, machine learning, and analysis of large clinical or registry datasets.
• Advanced proficiency in R programming and experience using Python, SQL, and modern data visualization tools.
• Experience leading complex analyses for peer-reviewed publications, scientific abstracts, and presentations.
• Experience serving as a scientific collaborator with investigators and multidisciplinary research teams.
• Experience supporting competitive grant applications through development of statistical analysis plans, study design, sample size calculations, methodology sections, tables, figures, and interpretation of results.
• Demonstrated experience contributing to or leading manuscript preparation for publication in peer-reviewed journals.
• Experience working with large multi-institutional, registry-based, or real-world healthcare datasets.

Requirements

• Minimum Education Level: Bachelor's Degree in data science, mathematics, statistics, computer science, or related quantitative field.
• Preferred Education Level: Master's Degree.
• Minimum Experience Required:
  • Bachelor’s degree in a quantitative field and more than 5 years of experience in quantitative analytics and applied data science OR
  • Master’s or Doctorate degree in a quantitative field and more than 3 years of experience in quantitative analytics and applied data science.
• Training Required:
  • Strong programming skills in development of AI/ML, Natural Language Processing (NLP) and statistical modeling applications.
  • Strong proficiency programming in R, Python, or adjacent languages.
  • Experience writing SQL queries, mining large datasets (pandas/dplyr), and using data visualization tools (matplotlib/ggplot2/plotly).

Benefits

• Salary Range: $108,492.80 - $165,422.40
• Actual compensation may vary based on location and a variety of job-related factors, including experience, skills, education, and internal equity among Team Members in similar positions.
• Commitment to maintaining fair and equitable pay practices and regularly reviewing compensation to ensure alignment across the workforce.