Senior Data Scientist
Johnson & Johnson•Santa Clara, CA
•Hybrid
About The Position
Johnson & Johnson MedTech Surgery is seeking an experienced Senior Data Scientist, Service Innovation, to advance the service data strategy for connected medical device platforms. This role will develop scalable data models, analytics pipelines, and AI-enabled insights that improve service operations, device reliability, and customer outcomes. The Senior Data Scientist will partner across Service, R&D, Engineering, Quality, Regulatory, IT, and Data Platform teams to define service data requirements, influence structured device logging, and deliver analytics solutions across the service ecosystem. The role will complement enterprise data platform capabilities by shaping service-specific models, integration requirements, and analytical use cases rather than recreating platform services.
Requirements
- Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, or a related technical field.
- 5+ years of experience in data science, data engineering, analytics, or a related role, including hands-on work with large-scale datasets and distributed processing systems.
- Advanced proficiency in Python and SQL for data processing, statistical analysis, machine learning, and query optimization.
- Hands-on experience with Apache Spark or comparable distributed data frameworks and notebook-based analytics environments such as Databricks.
- Experience designing analytical data models, including relational, dimensional, and time-series structures.
- Strong knowledge of statistical methods, feature engineering, model evaluation, and analytical validation.
- Experience developing or supporting governed data pipelines and analytics-ready datasets in cloud environments such as AWS or Azure.
- Ability to translate service and business use cases into technical data, telemetry, and analytical requirements.
- Strong written and verbal communication skills for documentation, stakeholder engagement, and explanation of complex technical concepts to non-technical audiences.
- Demonstrated ability to work effectively in cross-functional, matrixed environments and manage ambiguity while driving outcomes.
Nice To Haves
- Experience with IoT, connected products, device telemetry, or high-volume machine log data.
- Experience in medical devices, healthcare, or another regulated industry, including support for compliant and auditable data systems.
- Knowledge of FDA, EU MDR, GxP, computer system validation, cybersecurity, data privacy, and data governance principles.
- Experience integrating data across ERP, CRM, service, and reporting platforms.
- Experience with Power BI or comparable visualization tools and with defining operational KPIs.
- Experience with predictive maintenance, anomaly detection, failure prediction, root cause analysis, or service operations analytics.
- Experience with Databricks, Spark, Delta Lake, workflow orchestration, and cloud object storage.
- Ability to support multi-device, multi-platform analytics architectures and collaborate with enterprise data platform teams.
Responsibilities
- Define and execute a service data strategy aligned with Service Operations priorities and the Service Digital Innovation Roadmap.
- Design and maintain scalable analytical data models for device telemetry and logs, service and maintenance workflows, and customer interaction data.
- Partner with R&D and Engineering to translate service use cases into structured logging requirements, telemetry specifications, schemas, and data contracts.
- Influence device-agnostic data structures and governance standards that support service use cases across multiple products and platforms.
- Develop predictive and diagnostic models for device performance monitoring, failure prediction, root cause analysis, and service resource optimization.
- Apply statistical methods, machine learning, and AI techniques to large-scale service datasets, with appropriate validation, monitoring, and documentation.
- Partner with IT and Data Platform teams to integrate, normalize, validate, and serve service data through governed enterprise platforms and analytics-ready datasets.
- Integrate data across connected devices and enterprise systems, including ERP, CRM, and service platforms, while maintaining lineage, quality, and role-based access.
- Define service KPIs and support dashboards, reporting, and analytical products that translate data into actionable recommendations.
- Communicate findings, tradeoffs, and recommendations to technical and business stakeholders, and drive adoption through documentation, training, and cross-functional collaboration.
- Ensure analytical solutions and data processes support auditability, cybersecurity, privacy, and applicable quality and regulatory requirements.
Benefits
- Vacation –120 hours per calendar year
- Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
- Holiday pay, including Floating Holidays –13 days per calendar year
- Work, Personal and Family Time - up to 40 hours per calendar year
- Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
- Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
- Caregiver Leave – 80 hours in a 52-week rolling period
- Volunteer Leave – 32 hours per calendar year
- Military Spouse Time-Off – 80 hours per calendar year
- Consolidated retirement plan (pension)
- Savings plan (401(k))
- Long-term incentive program
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What This Job Offers
Job Type
Full-time
Career Level
Senior
