Data Scientist

Job Summary:

This position is for a Data Scientist role within a multidisciplinary team focused on applying advanced data science methods in vision research. The Data Scientist will play a critical role in processing and analyzing large datasets from biological and medical research, focusing on modeling and visual analytics to address key questions in translational vision science.

Specific responsibilities include:
1) Developing and optimizing machine learning models, including neural networks (e.g., CNNs and XGBoost), to analyze electrophysiological data, predict trends, and support decision-making.
2) Conducting statistical analyses, including hypothesis testing and predictive modeling, to generate actionable insights.
3) Collaborating with interdisciplinary teams to develop research publications and present findings at international conferences.
4) Supporting the development of novel computational tools for retinal data analysis.

Minimum Qualifications:

PhD in Applied Statistics or related field.

Preferred Qualifications:

Expertise in Python (NumPy, Pandas, PyTorch, Scikit-learn), R, and SQL. Experience with machine learning models such as Random Forests, SVMs, and XGBoost. Strong background in statistical analysis and hypothesis testing. Proficiency in data visualization tools (e.g., Matplotlib, Seaborn). Familiarity with biological data analysis and interdisciplinary research collaboration. Publication record showcasing expertise in applying computational models to complex systems. Strong communication skills, with experience presenting complex findings to non-technical audiences.

Work Days:

Monday - Friday; Some evening or weekend hours may be required

Message to Applicants:

Salary Range-$50,000-$60,000

Recruitment Office: Human Resources

We are an Equal Opportunity Employer.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status or disability or other protected classes under State and Federal law.