Associate Director, Data Science - Oncology Biomarkers & AI

Merck; Boston (MA); On-site; USD 160,000 - 251,000; Full time

Benefits offered by this job

Annual bonus

Long-term incentive

Medical insurance

Dental insurance

Vision care

401(k)

Job summary

Merck's Translational Genome Analytics group is recruiting an Associate Director to join our data science team. You will perform data mining of molecular data and inform decisions across our oncology pipeline.

You will analyze multi-modal clinico-genomic data and apply deep learning to identify biomarkers and guide therapies, collaborating across AIML teams. The role requires advanced degree and substantial computational experience; strong communication and collaboration are essential.

Qualifications

• Master's or PhD with a strong computational and statistical component in pharma/biotech or related field.
• Extensive experience in data mining and statistical learning for multimodal molecular profiling datasets.
• Proficiency in scientific computing environments (R/Python, Matlab) and reproducible analyses.
• Experience applying deep learning/inference frameworks to oncology or related therapeutic areas.

Responsibilities

• Enable reverse translation from clinical datasets to inform biomarker discovery and strategies.
• Analyze and visualize findings from large clinico-genomic datasets (RNAseq, WES/WGS, imaging, proteomics).
• Leverage deep learning and multivariate modeling to discover biomarkers predicting clinical outcomes.
• Collaborate with AIML teams on development of foundation models using large cohorts.

Skills

Statistical learning

Data mining

Multimodal data analysis

R

Python

MATLAB

Deep learning

Biomarker discovery

Education

Master's with 8+ years

Ph.D. with 4+ years

Tools

R

Python

MATLAB

Job description

Merck's Translational Genome Analytics group is recruiting an Associate Director to join our data science team. You will perform data mining of molecular data and inform decisions across our oncology pipeline.

You will analyze multi-modal clinico-genomic data and apply deep learning to identify biomarkers and guide therapies, collaborating across AIML teams. The role requires advanced degree and substantial computational experience; strong communication and collaboration are essential.