Data Scientist

University of Colorado Anschutz; Denver (CO); Hybrid; USD 60,225 - 90,171; Full time

Benefits offered by this job

Medical: Multiple plan options

Dental: Multiple plan options

Tuition Benefit

Job summary

A major public educational institution in Denver is seeking a Data Scientist to develop machine-learning models from EEG data for early detection of Alzheimer's disease. The role involves exploratory data analysis and building reproducible pipelines using Python. Candidates should have a relevant Bachelor's degree and strong data analysis skills. The position supports a hybrid schedule with generous benefits, including medical coverage and a 401(a) retirement plan.

Qualifications

• Bachelor’s in a relevant field from an accredited institution.
• Two years of professional IT project management experience.
• Experience with time-series/signal data is preferred.

Responsibilities

• Document experiments and results clearly.
• Perform exploratory data analysis on sleep EEG datasets.
• Train, evaluate, and compare machine learning models.

Skills

Data Analysis

Machine Learning

Python

EEG Analysis

Education

Bachelor’s in Computer Science or related field

Master’s degree in a related field

Tools

scikit-learn

PyTorch

TensorFlow

Job description

Alzheimer’s disease is a leading cause of death in the United States, and scalable digital tools for prevention and early detection are urgently needed. Our team is building machine learning–driven digital biomarkers from wearable sleep electroencephalography (EEG) to assess neurodegenerative changes before symptoms appear.

We’re seeking a Data Scientist who can analyze real‑world datasets and build well‑documented, reproducible machine‑learning pipelines in Python. You will drive exploratory data analysis, feature engineering, and model development (scikit‑learn and preferably PyTorch, or a similar framework), while applying solid software practices that make results reliable and repeatable. Some examples of projects that the finalist might work on include brain aging phenotypes from EEG derived features, cognitive decline trajectories, linking oscillatory circuits to performance, and neuroimaging/biomarkers correlates, integrating EEG with Alzheimer’s molecular/structural measures.

Candidates with backgrounds in Biostatistics, Statistics, Computer Science, Applied Mathematics, Biomedical/Bioengineering, Electrical/Computer Engineering, Neuroscience, and/or Research Software Engineering who bring strong data‑analysis skills and practical ML experience are encouraged to apply. Equivalent real‑world experience is welcome.

Key Responsibilities

• Document experiments and results clearly; draft brief model cards and dataset summaries.
• Perform exploratory data analysis on sleep EEG and related datasets; define targets, features, and baselines.
• Train, evaluate, and compare models (classification/regression, cross validation, regularization, calibration, error analysis).
• Implement and tune ML pipelines (scikit learn; PyTorch/TensorFlow preferred for deep learning tasks).
• Keep data steps reproducible with configuration, run scripts, and sensible versioning of code/data.
• Build and maintain robust workflows to ingest, validate, and transform data into analysis ready formats.
• Other duties as assigned.

Work Location

Hybrid – this role is eligible for a hybrid schedule of 3 days per week on campus and as needed for in‑person meetings.

Why Join Us

The University of Colorado Anschutz Medical Campus is a public education, clinical and research facility serving 4,500 students, and a world‑class medical destination at the forefront of life‑changing science, medicine, and healthcare. CU Anschutz offers more than 42 highly rated degree programs through 6 schools and colleges, supported by $704 million in research awards in fiscal year 2023, creating an overall economic impact to the state of Colorado of $11.5 billion. We are the single largest health professions education provider in Colorado, awarding nearly 1,450 degrees annually. Powered by our award‑winning faculty, renowned researchers and a reputation for academic excellence, the CU Anschutz Medical Campus drives innovation from the classroom to the laboratory to the delivery of unparalleled patient care.

Benefits

• Medical: Multiple plan options
• Dental: Multiple plan options
• Additional Insurance: Disability, Life, Vision
• Retirement 401(a) Plan: Employer contributes 10% of your gross pay
• Paid Time Off: Accruals over the year
• Vacation Days: 22 / year (maximum accrual 352 hours)
• Holiday Days: 10 / year
• Tuition Benefit: Employees have access to this benefit on all CU campuses
• ECO Pass: Reduced rate RTD Bus and light rail service

Minimum Qualifications

• Bachelor’s in Computer Science, Electrical/Computer Engineering, Data Science, Statistics, Applied Math, Neuroscience, or a related field from an accredited institution.
• Two (2) years of professional IT project management experience, which included open source or AI/Machine Learning projects.
• Substitution: An advanced degree (Masters or Doctorate) may be substituted for experience on a year for year basis if the degree is in a field of study directly related to the work assignment.
• Intermediate:
  • Bachelor’s in Computer Science, Electrical/Computer Engineering, Data Science, Statistics, Applied Math, Neuroscience, or a related field from an accredited institution.
  • One (1) year of professional IT project management experience, which included open source or AI/Machine Learning projects.
  • Substitution: An advanced degree (Masters or Doctorate) may be substituted for experience on a year for year basis if the degree is in a field of study directly related to the work assignment.
• Entry:
  • Bachelor’s in Computer Science, Electrical/Computer Engineering, Data Science, Statistics, Applied Math, Neuroscience, or a related field from an accredited institution.

Preferred Qualifications

• Master’s degree in a related field
• Experience with time‑series/signal data (EEG, ECG, accelerometry) and libraries like MNE‑Python and YASA.
• Experience running or extending baseline machine learning workflows (scikit‑learn; familiarity with PyTorch or TensorFlow is a plus).
• Experience using tools that make research smoother: experiment tracking, data versioning, simple job scheduling (HPC/SLURM or equivalent).
• Experience with packaging and simple APIs/CLIs to share analysis tools, basic containerization.

Competencies: Knowledge, Skills, and Abilities

• Ability to communicate effectively, both in writing and orally and follow through.
• Ability to establish and maintain effective working relationships with employees at all levels throughout the institution.
• Python 3 for data science: pandas/NumPy for wrangling; scikit‑learn for modeling; experience with in Jupyter and modular code outside notebooks.
• Machine learning fundamentals: sound validation design (train/test splits, CV), prevention of leakage, metric selection, and interpretation.
• Frameworks: familiarity with PyTorch (preferred) or TensorFlow for deep learning; ability to read/modify training scripts.
• Software practices: Git/GitHub (branches, PRs), unit tests with pytest, environment management (conda/venv/poetry), Unix‑like shell.
• Data skills: joins/reshapes, basic statistics, simple SQL or structured‑data querying.
• Awareness of study design, uncertainty, and good reporting practices; experience with human‑subjects data privacy.
• Interest in sleep neurophysiology, brain aging, and neurodegeneration.

How to Apply

For full consideration, please submit the following document(s):

• A letter of interest describing relevant job experiences as they relate to listed job qualifications and interest in the position.
• Three to five professional references, including name, address, phone number (mobile number if appropriate), and email address.

Questions should be directed to: neurology‑[e-mail].

Please apply through our official job website portal: https://cu.taleo.net/careersection/2/jobdetail.ftl?job=38541&lang=en.

Screening of Applications Begins

Applications will be accepted until finalists are identified, but preference will be given to complete applications received by January 5, 2026. Those who do not apply by this date may or may not be considered.

Anticipated Pay Range

• Senior: $70,889–$90,171
• Intermediate: $65,572–$83,408
• Entry: $60,225–$76,645

Total Compensation Calculator

Your total compensation goes beyond the number on your paycheck. The University of Colorado provides generous leave, health plans and retirement contributions that add to your bottom line.

Equal Employment Opportunity Statement

CU is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities.

ADA Statement

The University will provide reasonable accommodations to applicants with disabilities throughout the employment application process. To request an accommodation pursuant to the Americans with Disabilities Act, please contact the Human Resources ADA Coordinator [e-mail].

Background Investigation

The University of Colorado Anschutz Medical Campus is dedicated to ensuring a safe and secure environment for our faculty, staff, students and visitors. To assist in achieving that goal, we conduct background investigations for all prospective employees.

Vaccination Policy

CU Anschutz strongly encourages vaccination against the COVID‑19 virus and other vaccine‑preventable diseases. If you work, visit, or volunteer in healthcare facilities or clinics operated by our affiliated hospital or clinical partners or by CU Anschutz, you will be required to comply with the vaccination and medical surveillance policies of the facilities or clinics where you work, visit, or volunteer, respectively. In addition, if you work in certain research areas or perform certain safety‑sensitive job duties, you must enroll in the occupational health medical surveillance program.