The University of Miami is seeking a Sr. Software Engineer to support high-impact, interdisciplinary research initiatives by applying advanced data science techniques to solve complex problems across diverse domains, including cybersecurity.
Requirements
- Proficiency in statistical modeling, machine learning, and data visualization techniques.
- Strong programming skills (e.g., Python, R, SQL) and familiarity with relevant data tools and frameworks.
- Knowledge of cloud computing platforms, big data technologies, or real-time data processing systems.
- Cybersecurity certification is highly preferred.
- Minimum 4 years of relevant experience in applied data science, analytics, software engineering or research settings.
- Highly preferred experience: in cybersecurity-related analytics or data-driven security research.
- Track record of contributing to research and innovation projects.
Responsibilities
- Executes and contributes to cutting-edge research projects in data analytics, with a focus on analytic automation, machine learning, predictive modeling, or large-scale data processing.
- Leads the development of a state-of-the-art data portal for the storage, management and analysis of multidimensional and diverse datasets.
- Leads the development of pipelines and workflows for the integration of publicly available datasets with the developed infrastructure.
- Leverage state-of-the-art big data and AI approaches and develop computational algorithms and workflows for the identification of novel targets and the prioritization of efficacious drug combinations.
- Mines and analyzes data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Leads the assessment of effectiveness and accuracy of new data sources and data gathering techniques.
- Develops custom data models and algorithms to apply to data sets.
Other
- Mentors and supports cybersecurity research team members in applying data analytics methodologies to ongoing projects.
- Collaborates with interdisciplinary teams and external stakeholders to design and implement data-driven solutions.
- Engages in collaborative research efforts with university departments, industry partners, and global research networks.
- Works closely with faculty, research collaborators, and external partners to drive data-driven discovery and innovation.
- Collaborates with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
