Data Scientist

Job Description Harris-Stowe State University is a historically Black institution (HBCU) located in the heart of vibrant mid-town St. Louis, Missouri. Harris-Stowe’s beautiful campus is minutes from the renowned Gateway Arch, St. Louis Zoo, St. Louis Art and History Museums, Forest Park, and other cultural and educational institutions. Harris-Stowe’s diverse faculty and staff provide a wide range of academic programs to one of the most culturally diverse student bodies in the St. Louis region. Job Summary: We are seeking a talented Data Scientist to analyze data from our research on the effects of light pollution. This is a limited-time position funded by a grant. The successful candidate will utilize advanced statistical and computational techniques to interpret complex datasets and contribute to understanding environmental impacts on reproductive health. Essential Functions: Strategic Leadership: Train and organize undergraduate researchers. Collaborate with researchers to design experiments and analyze results. Present findings to the research team and at conferences. Stay abreast of industry trends, emerging technologies, and best practices in neurobiology and data science. Program Development and Management: Analyze large datasets related to light pollution and outcomes. Develop and implement data models and algorithms. Order supplies associated with the projects' data analyses. Lead the planning, design, and launch of new grant-related protocols and procedures in line with industry standards. Quality Assurance: Conduct experiments related to light pollution effects under the guidance of senior researchers. Record, store, and manage experimental data accurately. Ensure compliance with safety and regulatory guidelines. Maintain a clean and organized lab environment. Faculty Support and Development: Assist in preparing laboratory reports and presentations. Plan and execute lab safety and procedure trainings. Provide guidance and support to faculty and undergraduate researchers in grant activities. Visualize data findings through charts, graphs, and reports. Ensure data integrity and security. Perform other duties as assigned by the PI of the grant. Minimum Education and Experience: Master’s degree or higher in Data Science, Statistics, Computer Science, Neuroscience, or a related field. Experience with statistical software (e.g., R, SAS, SPSS) and programming (e.g., Python, SQL). Strong analytical and problem-solving skills. Experience with data visualization tools (e.g., Tableau, Power BI). Excellent communication and teamwork skills. Prior neuroscience laboratory experience. Strong attention to detail and organizational skills. Ability to work independently and collaboratively. Qualifications: Master’s degree or higher in Data Science, Statistics, Computer Science, Neuroscience, or a related field. Knowledge, Skills, and Abilities: Knowledge Neuroscience fundamentals, including brain anatomy, neural networks, electrophysiology, neurodevelopment, and neurodegenerative diseases. Biological data types such as genomic, transcriptomic, proteomic, electrophysiological, imaging, neural spike trains, and behavioral datasets. Statistical methods including linear models, Bayesian methods, hypothesis testing, and handling biological variability. Bioinformatics, especially high-throughput sequencing data analysis, gene expression, and protein interaction networks. Data ethics and security, including privacy regulations and secure data handling. Skills Programming in Python, R, MATLAB, Julia; experience with relevant libraries. Data wrangling, preprocessing, and organizing large datasets. Advanced statistical analysis skills. Data visualization expertise. Neuroimaging analysis skills. Machine learning implementation for neurobiological data. Algorithm development for neurobiological applications. Experience with high-performance computing and cloud platforms. Abilities Critical thinking and problem-solving. Interdisciplinary collaboration and effective communication. Data interpretation within neurobiology context. Attention to detail and data quality assurance. Curiosity and innovation in neurobiological research. Data integration from diverse datasets. Effective visualization and communication of findings. Adaptability to new tools and methods. "Please No Phone Calls" Due to high application volume, only shortlisted candidates will be contacted for interviews. No phone inquiries. EOE Statement Harris-Stowe State University is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, age, disability, veteran status, or gender identity/expression. The above statements describe the general nature of the work and are not exhaustive. Management reserves the right to amend responsibilities as needed.

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