DataTecnica
| Remote/Flexible/Hybrid | Full-time (2,000 hours per year contracting)
About the Role
We’re seeking a Modifiable Risk Factors Researcher to drive high-throughput epidemiological analyses at biobank scale for the NIH’s Center for Alzheimer’s and Related Dementias (CARD). You’ll design and execute large-scale observational and genetic epidemiology studies investigating modifiable and environmental risk factors for Alzheimer’s disease and related dementias, working primarily within the UK Biobank and All of Us research platforms. The role combines classical epidemiological methods with modern genomic, proteomic, and machine learning approaches to identify actionable targets for dementia prevention in a highly collaborative environment.
What You’ll Do
Primary Responsibilities (85%)
- Design and execute high-throughput epidemiological analyses of modifiable risk factors (cardiometabolic, lifestyle, environmental, pharmacological exposures) for AD and related dementias at biobank scale (200K–500K+ participants)
- Work extensively within the UK Biobank Research Analysis Platform (RAP) and the All of Us Researcher Workbench to conduct phenotype-wide and exposure-wide association studies
- Integrate proteomic data (e.g., Olink, SomaScan) to identify circulating protein biomarkers associated with modifiable risk factors and dementia risk
Secondary Responsibilities (15%)
- Support GWAS for risk and progression phenotypes related to AD and related dementias
- Collaborate with bioinformatics team on multi-omic follow-up of data mining signals
Required Qualifications
Preferred Qualifications
- Experience with Alzheimer’s, Parkinson’s, or neurodegenerative disease epidemiology or genetics
- Experience analyzing proteomic data at scale (Olink Explore, SomaScan, UK Biobank Pharma Proteomics Project)
- Applied machine learning experience in biomedical or epidemiological contexts (scikit-learn, XGBoost, survival ML, or equivalent)
- Experience with pharmacoepidemiology or drug-repurposing study designs
- Familiarity with longitudinal phenotype analysis and time-to-event methods
- Experience integrating multi-ancestry data
Technical Environment
You’ll work primarily within the UK Biobank Research Analysis Platform and the All of Us Researcher Workbench, with additional access to cloud-native analytics environments including Terra and Verily Workbench. Familiarity with WDL/Cromwell or Nextflow workflows is a plus. We leverage both CPU and GPU compute for large-scale analyses in the cloud.
To Apply
Apply here on linked in. After the initial review process we will ask you to formally submit your CV and cover letter with links to 2–3 representative publications demonstrating biobank-scale epidemiological research or related methodology, as well as any relevant GitHub content prior to an interview.
Compensation
$100,000 to $200,000 / year total compensation commensurate with experience. Multiple positions at various levels of seniority exist for this role.
About DataTecnica
DataTecnica is a biomedical datascience, AI and software company specializing in analytics for neurological and other diseases. We work at the intersection of large-scale genomics, clinical data, and translational research—partnering with major initiatives from academia and non-profits to tech including the NIH’s Center for Alzheimer’s and Related Dementias (CARD). Our team has contributed to over 500 peer-reviewed publications in neurogenetics and neurodegenerative disease research.
