Associate Principal Data Scientist - Early Cardiovascular, Renal and Metabolism

AstraZeneca; Boston (MA); On-site; USD 143,000 - 215,000; Full time

Benefits offered by this job

Incentives & equity

Retirement programs

Paid time off & benefits

Job summary

AstraZeneca plc in Boston, MA is seeking an Associate Principal Data Scientist to connect biomarker and multi-omics data with drug discovery decisions, onsite in Boston.

You will analyze large and complex datasets, validate targets, and identify biomarkers to support disease modulation and patient stratification, collaborating with internal and external partners to translate results into actionable insights for drug development.

Qualifications

• PhD or equivalent in bioinformatics, systems biology, statistics, data science or related field.
• 6 years of experience.
• Proven knowledge of cardiovascular, renal or metabolism biology and related data.
• Experience using computational, statistical and ML techniques for large datasets.
• Proficiency in R and Python, with Unix/Linux and shell scripting.
• Excellent consulting, communication and presentation skills.

Responsibilities

• Analyze large, complex biomarker and multi-omics datasets to support target identification and validation.
• Validate drug targets using data-driven approaches.
• Identify novel biomarkers to support disease modulation and patient stratification.
• Integrate genetics, omics, clinical data and EHR for insights.
• Collaborate with internal and external partners to access and apply data sources.
• Translate analytical results into actionable findings for drug discovery and development.

Skills

Statistical data analysis

Machine learning

Data visualization

Communication/presentation

Education

PhD or equivalent experience

Tools

R

Python

Unix/Linux

Shell scripting

Job description

The Associate Principal Data Scientist role supports AstraZeneca’s Early Cardiovascular, Renal and Metabolism (CVRM) Data Science & AI Department, working on analyses that connect complex biomarker and multi-omics data to drug discovery decisions. The position is based in Boston, MA with an onsite work arrangement.

Role Summary

In this position, you will analyze large and complex exploratory biomarker datasets and multi-omics and clinical information to validate and identify drug targets and biomarkers. Your work will contribute to understanding disease modulation and supporting patient stratification through data-driven insights.

Key Responsibilities

• Analyze and interpret large, complex datasets, including exploratory biomarker data from clinical trials.
• Validate existing drug targets using data-driven approaches.
• Identify novel drug targets and biomarkers that support disease modulation and patient stratification.
• Integrate and analyze big data sources such as genetics, dynamic omics, clinical observations, and electronic health records.
• Collaborate with internal and external partners to access, evaluate, and apply relevant data sources.
• Translate analytical results into findings that support drug discovery and development.

Required Qualifications

• PhD or equivalent experience with a strong quantitative background in areas such as bioinformatics, systems biology, statistics, data science, or other quantitative sciences.
• 6 years of experience.
• Profound knowledge of cardiovascular, renal, or metabolism disease biology, including experience analyzing associated molecular and exploratory clinical data.
• Experience using computational, statistical, and machine learning techniques for the manipulation, visualization, and analysis of large complex datasets.
• Proficiency in R and Python, with experience in Unix/Linux and shell scripting.
• Excellent consulting, communication, and presentation skills.

Technologies

• R
• Python
• Unix/Linux
• Shell scripting

Desirable Skills and Experience

• Understanding of biological systems and signaling involved in cardiometabolic disease.
• Knowledge of statistical data analysis methods, including experimental design, linear and nonlinear models, mixed effect models, exploratory biomarkers, diagnostic analyses, applied Bayesian statistics, data mining, multivariate data analysis, and statistical learning.
• Experience leading statistical analysis projects aligned to drug discovery.

Compensation

USD 143,323 - 214,984 per year.

Benefits

• Eligible for various incentives, including short-term incentive bonuses, equity-based awards for salaried roles, and commissions for sales roles.
• Qualified retirement programs.
• Paid time off, including vacation, holidays, and leaves.
• Health, dental, and vision coverage.

Where to Learn More

• Follow AstraZeneca on LinkedIn.
• Follow Alexion on LinkedIn.
• Follow AstraZeneca on Facebook.
• Follow AstraZeneca on Instagram.
• Learn more about Alexion at www.alexion.com.