Data Scientist

Key Skills

Data Analysis, Data Analytics, Data science techniques, Data Visualization, Deep Learning, Design, Effective communication skills, Jupyter Notebook, Linux Operating system, Machine learning techniques, Project management, Python Programming, R Programming, RStudio, SPSS Statistics, SQL, Statistics

Job Description

The mission of the Yale Institutional Biorepository Program is to establish a centralized biorepository with a high quantity and quality of human biospecimens and associated databases to advance future biomedical research, accelerate discoveries, and improve treatments for patients. The program is seeking highly motivated and experienced Data Scientists with a strong background in data analytics and statistics. Successful candidates will have the opportunity to work in a multidisciplinary environment, help researchers with data integration and management, and develop pipelines to empower data analysis throughout the entire scientific and translational research process within the Biorepository and the Yale research community. The applicant will also have the opportunity to present/publish the results in scientific conferences/journals, interact with world-class scientists, design, and execute analysis independently and collaboratively with other scientists. A strong interest in learning new programming languages and environments, tools, basic biology, etc., is a must.

Responsibilities:

Collect, manage, and govern different types of data, such as clinical and genomic data, from various sources and integrate these interoperable data into an all-in-one system, making them readily available to the broader research community.

Conduct routine data quality and consistency checks and resolution of data discrepancies.

Work with other scientists to develop and apply statistically rigorous solutions for study design, data analysis, and information mining of omics and other biological data for the discovery of clinically actionable biomarkers, integration of these data with clinical information, and translation of genomic discoveries to the bedside to accelerate precision medicine.

Work with the bioinformatics and software engineer team to design, build, and operate software platforms and infrastructure for managing, distribution, and scalable data analysis in the repository.

Assist in preparation of grant proposals, participate in publications and presentations as author or co-author

NOTE: This job description is not intended to provide a comprehensive or exclusive list of job duties. Job duties and/or responsibilities within the context of this job description may change at the discretion of the employee's direct supervisor.

Essential Duties

Develop and execute new and/or highly complex algorithms and statistical predictive models and determine analytical approaches and modeling techniques to evaluate potential future outcomes. Establish analytical rigor and statistical methods to analyze large amount of data, using advanced statistical techniques and mathematical analyses. Manage analytical projects from data exploration, model building, performance evaluation, through implementation. Develop work plans and monitor progress and project timelines. Document coding and changes to work plans using established work group methods in GitHub.Interact with a multidisciplinary team of internal and external peers to regularly, effectively, and openly communicate progress and outcomes of planned work. Attend weekly team meetings to discuss team and project-related activities, issues, change, communications, and updates.

Required Education and Experience

Master’s Degree in computer science, applied/computational mathematics, engineering, biostatistics, statistics, or a quantitative field such as astronomy or geology, and 2 years of hands-on experience in deep learning or an equivalent combination of education and experience.

Required Skill/Ability 1:

Experience working in the field of data science/data analytics and statistics.

Required Skill/Ability 2:

Proficient in data collection, cleaning, formatting, visualization, analysis, and reporting. Experience in programming/coding using Python, R, and SQL.

Required Skill/Ability 3:

Proficiency with Anaconda, Jupyter, Spyder, RStudio, SPSS, and Excel. Experience with Linux and Windows operating systems.

Required Skill/Ability 4:

Capability to work independently or collaboratively in a teamwork environment.

Required Skill/Ability 5:

Excellent written, verbal, and presentation skills. Excellent management skills.

Preferred Education, Experience and Skills:

Familiar with collecting clinical data and imaging from different medical databases and resources. Experience with machine learning and deep learning for predictive statistics and outcomes. Familiar with data visualization using Tableau and other data visualization platforms. Experience in mentoring and advising trainees.

Drug Screen

No

Health Screening

No

Background Check Requirements

All candidates for employment will be subject to pre-employment background screening for this position, which may include motor vehicle, DOT certification, drug testing and credit checks based on the position description and job requirements. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process visit Learn about background checks under the Applicant Support Resources section of Careers on the It's Your Yale website.

COVID-19 Vaccine Requirement

The University maintains policies pertaining to COVID-19. All faculty, staff, students, and trainees are required to comply with these policies, which may be found here:

https://covid19.yale.edu/health-guidelines

Posting Disclaimer

The intent of this job description is to provide a representative summary of the essential functions that will be required of the position and should not be construed as a declaration of specific duties and responsibilities of the particular position. Employees will be assigned specific job-related duties through their hiring departments.

EEO Statement:

University policy is committed to affirmative action under law in employment of women, minority group members, individuals with disabilities, and protected veterans. Additionally, in accordance with Yaleís Policy Against Discrimination and Harassment, and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individualís sex, sexual orientation, gender identity or expression, race, color, national or ethnic origin, religion, age, disability, status as a special disabled veteran, veteran of the Vietnam era or other covered veteran.