Why Mayo Clinic
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.
Benefits Highlights - Medical: Multiple plan options.
- Dental: Delta Dental or reimbursement account for flexible coverage.
- Vision: Affordable plan with national network.
- Pre-Tax Savings: HSA and FSAs for eligible expenses.
- Retirement: Competitive retirement package to secure your future.
ResponsibilitiesPosition Overview
Data Science Analysts at Mayo Clinic perform detailed analysis of large bodies of heterogeneous data to identify patterns and insights impacting patient health. This position is assigned to the Neurology AI program and focuses on developing workflows for medical imaging and electrophysiological data. This role emphasizes a collaborative, team-based approach to problem-solving, working closely with clinicians, informaticians, and technical partners to develop clinically meaningful solutions.
In addition to standard model development and analysis, this role requires a significant component of software and data engineering. The Data Science Analyst will develop and modify software to interface with existing systems that produce clinical data streams, supporting data management, extraction, and analysis.
Primary Responsibilities
Data Analysis & Modeling: Executes analytical procedures using machine learning, deep learning, statistical data processing, and signal processing techniques. Develops predictive models on datasets to address business and clinical problems.
Software & Data Engineering: Develops and modifies scripts or software applications to support data management and extraction. Interfaces with existing software systems to build workflows for medical imaging and electrophysiological data.
Consultation: Works with engineers, informaticians, and clinicians to develop and deploy analytic solutions for non-technical users. Provides data insights for problems approachable through analytics techniques using a consultative, team-oriented mindset.
Reporting & Communication: Contributes to the interpretation of data analysis and report writing. Presents findings to business or clinical practice stakeholders.
Support: Helps customers understand datasets and provides training or suggestions for improvement on data requests. May support scientific projects under the guidance of a senior-level data scientist.
QualificationsA Bachelor's degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative and a minimum of three years of professional or research experience in data science will be considered.
The preferred candidate will possess a Master's degree or a PhD in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field and a minimum of one year of professional or research experience in data.
Technical Competencies
Programming: Proficiency in Python is required. Exposure to Java or C is preferred for system interfacing.
Data Engineering: Experience with SQL and data warehousing/data lakes is required. Familiarity with Apache Spark or similar tools is preferred.
Signal Processing: Basic familiarity with time series analysis and signal processing methodologies.
Analytics: Demonstrated application of analytical tools and methodologies (e.g., machine learning, statistical packages, modeling). Experience with data modeling and data exploration tools.
Exemption StatusExempt
Compensation DetailEducation, experience and tenure may be considered along with internal equity when job offers are extended.; $99,070 -148,616 annually.
Benefits EligibleYes
ScheduleFull Time
Hours/Pay Period80
Schedule Detailsstandard weekday hours expected with flexibility This is a hybrid position and must be located within 100 miles of the Mayo Clinic campus in Rochester, MN for on-site expectations to be discussed at an interview.
Weekend Schedulenone expected
International AssignmentNo
Site Description Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is.
Equal Opportunity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the 'EOE is the Law'. Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.
RecruiterJill SquierQualifications:
A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative and a minimum of three years of professional or research experience in data science will be considered.
The preferred candidate will possess a Master's degree or a PhD in a relevant field such as engineering, mathematics, computer science, health science, or other analytical/quantitative field and a minimum of one year of professional or research experience in data.
Technical Competencies
Programming: Proficiency in Python is required. Exposure to Java or C is preferred for system interfacing.
Data Engineering: Experience with SQL and data warehousing/data lakes is required. Familiarity with Apache Spark or similar tools is preferred.
Signal Processing: Basic familiarity with time series analysis and signal processing methodologies.
Analytics: Demonstrated application of analytical tools and methodologies (e.g., machine learning, statistical packages, modeling). Experience with data modeling and data exploration tools.