This role pays less than
68%
of similar roles. Most pay
$176,937–$246,150
— the shaded band above.
At the midpoint, this role pays about
$186k
versus about
$212k
for comparable roles.
Based on 240 similar postings.
Employer
About Johnson & Johnson
Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices
Johnson & Johnson currently has
46 open roles
on FindRole.
Listed pay typically runs
$117,000–$201,250
across 42 roles with salary data.
Senior Manager, R&D Data, Data Science, and AI – Digital Health for Neuropsychiatry joins the Neuroscience Data, Data Science, and AI team to advance digital health innovation for neuropsychiatry. This role involves developing, validating, and operationalizing digital tools, novel endpoints, patient stratification approaches, and evidence strategies for mood, psychotic, cognitive, and related disorders. The position requires applying AI/ML, modeling, and longitudinal analytics to support clinical trial optimization while monitoring emerging technologies like digital phenotyping, remote assessment, passive sensing, and speech and language analytics. Key responsibilities include integrating multimodal data—including imaging, blood-based biomarkers, omics, and real-world data—to provide a holistic view of patients. The role requires expertise in advanced statistical modeling, Bayesian methods, causal inference, and ensuring compliance with global regulatory standards while collaborating with cross-functional teams to integrate digital solutions into clinical operations and trial designs.
AI
Machine Learning
GenAI
Data Science
Data Analytics
Model Lifecycle Management
Risk Assessment
Data Privacy
Statistical Computing
Data Visualization
Quality Assurance
Regulatory Compliance
FDA
EMA
ISO/IEC Standards
EU AI Act
Digital Health
Process Optimization
Data Architecture
Python
SQL
HL7 v2
FHIR R4
Gen AI
Data Pipelines
Data Integration
Data Transformation
Middleware
HIPAA Compliance
PHI Data Handling
Interoperability Standards
Python
Machine Learning
SQL
NLP
Data Science
Statistical Modeling
Deep Learning
A/B Testing
Data Mining
Cloud Platforms
Data Lakes
Relational Databases
Information Retrieval
Sentiment Analysis
Topic Modeling
Classification
Data Engineering
Data Science
Analytics
Python
R
SQL
Predictive Modeling
Natural Language Processing
LLM
GenAI
Classification
Data Infrastructure
KPIs
Quantitative Research
E-commerce
SQL
Python
R
Spark
Snowflake
Airflow
ML Ops
Experimentation Design
Causal Inference
Statistical Analysis
Data Pipelines
Monitoring Systems
Analytics Engineering