Overview
Description:
We are seeking a data scientist to apply advanced analytics and AI methods on EHR phenotyping data from clinicogenomic data sources such as UK Biobank (UKBB) and Alliance for Genomic Discovery (AGD) datasets, driving discovery through large-scale biobank analyses. The candidate will extract patient cohorts from the EHR data in order for Genome-wide Association Studies (GWAS) and related applications to extract actionable insights from AbbVie's rich biobank data resources.
Responsibilities:- UKBB, AGD data and other RWDRequired Skill 1: Data curation and mining using Linux command line
- Required Skill 2: Advanced analytics
- Required Skill 3: Advanced programming skills with writing reusable scripts (R, Python, Spark or SQL)
- Required Skill 4: Learn existing automated EHR-phenotyping using large longitudinal UK Biobank and AGD data
- Required Skill 5: strong communication and teamwork
- What years of experience, education, and/or certification is required? 2-3 (PhD), or 5 years (MSc)
- What is a nice to have (but not required) regarding skills, requirements, experience, education, or certification? Biostatistics, Genetics, experience with latest AI methodologies
- What is the environment that this person will be working in (i.e. group setting vs individual role)? Individual role within a collaborative team
- Other notable details about the environment from the hiring manager about this role?- advance the state-of-art Phenomics Data Science initiatives using large-scale real-world data
- What positions/background experience do you feel are successful in this role.- experienced data scientist/data engineers with interest in driving new mathematical solutions and innovation in line with business strategy and rapidly changing data streams
