IT Professional

Job Summary:

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.

Some examples of projects include the following:

• Brain aging phenotypes derived from EEG-based digital features
• Cognitive decline trajectories linking sleep-related physiology to performance
• Multimodal correlates, integrating EEG with neuroimaging and Alzheimer's molecular/structural measures

We're seeking a Part-Time Data Scientist who can analyze realworld datasets and build welldocumented, reproducible applied mathematical analysis pipelines in Python. You will drive exploratory data analysis, feature engineering, and model development, while applying solid documentation and coding practices that make results reliable and repeatable.

Candidates with backgrounds in Applied Mathematics who bring strong dataanalysis skills and practical ML experience are encouraged to apply. Equivalent realworld experience is welcome.

Key Responsibilities:

• Perform exploratory data analysis on sleep EEG and related datasets; define targets, features, and baselines aligned with digital biomarker goals.
• Develop, evaluate, and compare models for classification/regression using sound validation design, including cross-validation, regularization, calibration, and structured error analysis.
• Translate scientific questions into measurable model objectives and evaluation criteria, balancing performance with robustness and interpretability.
• Document experiments and results clearly; draft brief model cards and dataset summaries, including assumptions, limitations, and intended use.
• Build and maintain robust workflows to ingest, validate, and transform sleep EEG and related signals into analysis-ready formats.
• Implement preprocessing and feature-generation steps appropriate for wearable biosignals, with attention to data quality, artifact handling, and consistent labeling/alignment.
• Implement data quality checks and lightweight reporting to catch issues early (e.g., missingness, signal quality variation, label inconsistencies).
• Other Duties assigned

Work Location:

Remote - this role is eligible to work remotely, but the employee must be in the United States.

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.

Qualifications:

Minimum Qualifications

Applicants must meet minimum qualifications at the time of hire.

Entry

• Bachelor's in Computer Science, Electrical/Computer Engineering, Data Science, Statistics, Applied Math, Neuroscience, or a related field from an accredited institution.

  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

  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.

Preferred Qualifications

• Master's degree in a related field

• Applied math methods relevant to biosignals: coursework or project experience in time-series analysis, statistical learning, signal processing, numerical optimization, inverse problems, or stochastic processes-especially applied to noisy real-world data.

• Biosignal/EEG experience: exposure to EEG (sleep or otherwise) or related physiological signals (ECG, actigraphy, respiration); familiarity with common preprocessing/feature concepts (filtering, spectral features, artifact handling). Experience with tools such as MNE-Python, YASA, or comparable MATLAB/R toolboxes is a plus.

• Practical model evaluation skills: experience designing train/test splits and cross-validation for subject-level/time-series data; structured error analysis; calibration/thresholding concepts; ability to compare baseline statistical models and communicate tradeoffs.

• Research tooling & workflow maturity: experience with reproducible workflows (clean repo structure, scripted runs, configuration files), basic environment management, and/or experiment logging.

• Human-subjects / regulated data awareness: experience working with IRB-governed datasets, data use agreements, or privacy constraints (HIPAA-aligned handling where applicable).

• interest in sleep neurophysiology, brain aging, and neurodegeneration; enthusiasm for building practical, scalable digital biomarkers from wearable data.

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.

* Outstanding customer service skills.

* Applied mathematics foundation: strong grounding in linear algebra, probability, statistics, and numerical methods; ability to translate scientific questions into quantitative objectives and assumptions.

* Quantitative modeling & inference: comfort with regression/classification fundamentals, regularization concepts, model diagnostics, and uncertainty/variability; ability to reason about overfitting and generalization even when using simple baselines.

* Time-series / signal analysis mindset: familiarity with core concepts such as sampling, filtering, stationarity/nonstationarity, spectral methods (e.g., FFT/PSD concepts), feature extraction, and artifact/noise considerations in real-world signals.

* Programming for scientific computing (ramp-up supported): working proficiency in at least one scientific computing environment (Python, MATLAB, or R) and the ability to implement and test analysis routines; comfort learning and extending an existing Python codebase (NumPy/pandas-style workflows, basic scripting, Jupyter).

* Reproducible analysis habits: produces clear, well-organized analyses with documented assumptions, versioned outputs, and readable code; willing to follow team standards for structure, naming, and reviewability.

* Data handling & quality awareness: ability to clean, join/reshape, and validate multi-source datasets; recognizes common data issues (missingness, label alignment, outliers, leakage risks) and can implement basic checks.

* Communication & collaboration: can explain quantitative results to mixed audiences (scientists/clinicians/engineers), create clear figures/tables, and write concise summaries of methods, results, limitations, and next steps.

How to Apply:

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

1. A letter of interest describing relevant job experiences as they relate to listed job qualifications and interest in the position

2. Curriculum vitae / Resume

3. Three to five professional references, including name, address, phone number (mobile number if appropriate), and email address

Questions should be directed to: neurology-hr@cuanschutz.edu

Please Note: The position has an end date of Nov 30^th due to NIH budget cycle, with the possibility of an extension

Screening of Applications Begins:

Applications will be accepted until finalists are identified, but preference will be given to complete applications received by February 16, 2026. Those who do not apply by this date may or may not be considered.

Anticipated Pay Range:

The starting salary range (or hiring range) for this position has been established as:

• Entry Level: $28.95-$36.84 per hour.
• Intermediate: $31.52-$40.00 per hour.

The above salary range (or hiring range) represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. This position may be eligible for overtime compensation, depending on the level.

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.

Total Compensation Calculator

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 at hr.adacoordinator@cuanschutz.edu.

Background Check Statement:

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 Statement:

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.