below marketmost similar roles pay hereabove market
This role pays more than
82%
of similar roles. Most pay
$137,100–$185,718
— the blue band above.
At the midpoint, this role pays about
$204k
versus about
$161k
for comparable roles.
Based on 240 similar postings.
Employer
About Genentech
Genentech is a leading research-driven company dedicated to discovering and developing, manufacturing, and commercializing medicines for people with serious and life-threatening diseases.
Genentech currently has
36 open roles
on FindRole.
Listed pay typically runs
$146,000–$271,100
across 18 roles with salary data.
The Senior Data Scientist (AI-assisted Clinical Development) joins the Innovation Accelerator team to build and deploy AI/ML-powered digital solutions for medicine development. This role involves partnering with product managers and software engineers to design, test, and scale statistical capabilities that extract insights from clinical, operational, and real-world data. Key responsibilities include applying advanced machine learning methods to support evidence generation, trial design, and decision support. You will build model development pipelines, ensure traceability, and integrate algorithms into production applications. Required skills include proficiency in Python or R, experience with scikit-learn, XGBoost, TensorFlow, or PyTorch, and knowledge of experimental design. The work focuses on solving complex scientific problems through automated workflows, simulation studies, and interpretable ML architectures within regulated healthcare environments.
What does a Data Scientist earn?
Median $173200 from 338 postings across 66 companies.
Apply advanced statistical and machine learning methods to develop tools for evidence generation and trial design.
Translate scientific problems into automated data science workflows and productized software solutions.
Build and maintain model development pipelines ensuring traceability, performance monitoring, and reproducibility.
Integrate models and algorithms into production applications in collaboration with engineering and product teams.
Design compliant and interpretable ML product architectures for regulated clinical development environments.
Create documentation templates to communicate modeling decisions, trade-offs, and performance summaries to stakeholders.
Act as a subject matter expert for simulation studies and comparative evaluations of analytical approaches.
What we're looking for
You have a Master’s or PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Bioinformatics, or a related field.
You have 3+ years of experience applying machine learning and statistical modeling to data-centric problems in research or product environments.
You are proficient with Python or R, including experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
You have experience in experimental design, simulation, and evaluation of model performance.
You have practical experience with version control, testing frameworks, and collaborative software development.
You have experience working with one or more of the following: RWD/RWE, decision analysis, clinical biomarkers, Bayesian inference, or interpretable ML.
You have excellent verbal and written communication skills to explain complex technical concepts in clear language.
Experience contributing to ML product pipelines, evidence synthesis models, or generative AI tooling (preferred).
Python
R
Machine Learning
Generative AI
TensorFlow
PyTorch
scikit-learn
Bayesian Methods
ML Ops
Agile
Stan
PyMC
brms
Data Pipelines
Statistical Modeling
Causal Inference
Cloud-native ML
Data Governance
Simulation Studies
Data Science
Machine Learning
Predictive Modeling
Statistical Modeling
Simulation
Data Engineering
MLOps
Numerical Methods
Design of Experiments
Data Pipelines
data-governance
data, lineage
Laboratory Data Systems