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Clinical Data Partnerships & Acquisition Lead

Philips
10-15 years
Not Disclosed
Bangalore, India
-10 June 15, 2026
Job Description
Job Type: Full Time Education: Bachelor’s or Master’s degree in Technical , Life Sciences , Biology, Biochemistry, Molecular Biology Skills: Causality Assessment, Clinical SAS Programming, Clinical Trials, Detail-Oriented, Drug Development, Lifesciences, Negotiation Skills, Regulatory Compliance, Communication Skills, CPC Certified, Data Analysis, Document Management, Life Science, Regulatory Compliance, Waterfall Model, GCP guidelines, ICD-10 CM Codes, CPT-Codes, HCPCS Codes, ICD-10 CM, CPT, HCPCS Coding, ICH guidelines, ICSR Case Processing, Interpersonal Skill, Labelling Assessment, MedDRA Coding, Medical Billing

Role Overview

The Clinical Data Partnerships & Acquisition Lead is a senior clinical leadership role within the Data & AI organization, responsible for enabling and accelerating clinical data acquisition. The role focuses on removing bottlenecks across site onboarding, clinical alignment, and data acquisition workflows while ensuring collaboration among clinical, field, partnership, and Data & AI teams.

The incumbent acts as a central orchestrator, aligning clinical requirements with data and AI needs to support scalable, high-quality data acquisition programs.


Role Scope & Operating Model

Direct Accountability

Data Acquisition Leadership

  • Orchestrate end-to-end data acquisition workflow readiness and execution.
  • Identify, track, and resolve bottlenecks throughout the data acquisition lifecycle.
  • Ensure alignment between clinical requirements and Data & AI objectives.
  • Drive workflow initiation and tracking through contracting platforms (e.g., Orion).

Delivered in Partnership

This role collaborates closely with:

Field Application Specialists

  • Protocol execution
  • Site operations
  • Clinical workflow implementation

Clinical Science Teams (Business Unit & Field)

  • Study design
  • Clinical validation
  • Scientific oversight

Clinical Partnerships Leader & Market Teams

  • Site engagement
  • Relationship management
  • Clinical network development

Data & AI Teams

  • Data requirements definition
  • Dataset usability validation
  • AI/ML readiness

External Stakeholders

(Engaged through partnership teams)

  • Hospitals
  • Imaging centers
  • Research institutions

Key Responsibilities

1. Clinical Data Acquisition Enablement

Site Identification & Onboarding

  • Support identification of clinical data sources.
  • Enable onboarding of hospitals, imaging centers, and research sites.
  • Collaborate with clinical and field teams on site readiness assessments.

Data Acquisition Acceleration

  • Remove process inefficiencies and coordination barriers.
  • Accelerate acquisition timelines and data availability.

2. Stakeholder Coordination & Clinical Interface

Cross-Functional Coordination

  • Serve as the central coordination point between:
    • Clinical teams
    • Field teams
    • Data & AI teams

Requirements Translation

  • Convert clinical needs into structured data requirements.

Dataset Development Support

Support creation of datasets for:

  • AI/ML model development
  • Clinical validation studies
  • Regulatory submissions
  • Product performance evaluation

3. Workflow & Process Orchestration

Workflow Management

  • Initiate and track workflows in contracting systems such as Orion.
  • Monitor workflow progress and escalation points.

Readiness Coordination

Ensure readiness of:

  • Data collection criteria
  • Case selection requirements
  • Clinical documentation requirements

Coordinated Activities

Coordinate (without direct ownership):

Protocol Readiness

  • Owned by Clinical Application Specialists

Data Preparation Activities

  • Annotation
  • Classification
  • Data organization
  • Dataset preparation

4. Data Lifecycle Execution

Enable and accelerate activities performed by responsible owners:

Site Operations

  • Site feasibility assessments
  • Site selection activities

Study Planning

  • Data Management Plan (DMP) inputs
  • Clinical data collection planning

Regulatory & Ethics Support

  • IRB (Institutional Review Board) processes
  • IEC (Independent Ethics Committee) approvals
  • Consent management processes

Contracting Support

  • Agreement preparation
  • Contract negotiations
  • Workflow progression

Alignment Activities

Ensure consistency among:

  • Clinical requirements
  • Regulatory requirements
  • Data & AI requirements

5. Governance, Compliance & Data Quality

Compliance Oversight

Ensure adherence to:

  • Clinical protocols
  • Study requirements
  • Ethics frameworks
  • Patient consent requirements
  • Privacy regulations
  • Regulatory standards

Data Quality Contributions

Provide clinical input for:

Data Quality & Usability

  • Dataset fitness for purpose
  • Clinical relevance

Data Standards

  • Imaging standards
  • Metadata standards

Data Protection

  • Anonymization processes
  • Privacy compliance

6. Bottleneck Resolution & Operational Acceleration

Bottleneck Management

Identify and resolve issues related to:

Site Onboarding

  • Site activation delays
  • Operational readiness issues

Ethics & Approvals

  • IRB/IEC review timelines
  • Consent-related delays

Data Readiness

  • Data quality issues
  • Data usability concerns
  • Workflow inefficiencies

Continuous Improvement

  • Drive process improvements aligned with the Data Chain RACI model.
  • Enhance scalability and operational efficiency.

Key Stakeholder Interfaces

Internal Stakeholders

Data & AI Organization

  • Data Managers
  • Data Architects
  • AI Teams
  • Data Science Teams

Clinical Teams

  • Clinical Science Teams (BU & Field)
  • Clinical Application Specialists

Commercial & Partnership Teams

  • Clinical Partnerships Leader
  • Market Teams
  • Sales Teams

Corporate Functions

  • Legal
  • Privacy
  • Regulatory Affairs
  • Intellectual Property & Security (IP&S)

External Stakeholders

(Through Partnership Model)

  • Hospitals
  • Imaging Centers
  • Research Institutions
  • Clinical Research Networks

Required Qualifications

Education

Advanced degree in:

  • Radiology
  • Clinical Sciences
  • Biomedical Engineering
  • Related healthcare or scientific discipline

Professional Experience

Overall Experience

  • 10–15 years of relevant industry experience

Required Experience Areas

  • MRI clinical domain
  • Radiology workflows
  • Clinical research
  • Hospital engagement
  • Clinical operations
  • Data acquisition programs

Domain Expertise

Clinical & Imaging Expertise

  • MRI protocols
  • Radiology workflows
  • Clinical operations

Clinical Research Knowledge

  • Study protocols
  • Informed consent processes
  • IRB/IEC procedures

Healthcare Ecosystem Knowledge

  • Hospital workflows
  • Clinical stakeholder engagement
  • Healthcare operations

Healthcare Data Systems

  • DICOM
  • PACS
  • EMR/EHR
  • RIS

Required Skills & Competencies

Stakeholder Management

  • Strong relationship-building abilities
  • Effective engagement across clinical and technical teams

Clinical-to-Data Translation

  • Ability to transform clinical requirements into structured data specifications

Execution Excellence

  • Strong project execution capability
  • Problem-solving and issue resolution skills

Collaboration

  • Experience working across global, cross-functional teams

Governance & Compliance Knowledge

Knowledge of:

  • HIPAA
  • GDPR
  • Healthcare privacy regulations
  • Clinical data governance frameworks

Preferred Qualifications

AI & Advanced Data Programs

  • Experience supporting AI/ML data initiatives
  • Exposure to clinical data platforms

Workflow Tools

Experience with:

  • Orion contracting workflows
  • Similar data lifecycle management tools

Emerging Technologies

Knowledge of:

  • Synthetic data approaches
  • Federated learning methodologies

Success Metrics (KPIs)

Operational Efficiency

  • Reduction in data acquisition cycle time
  • Faster workflow turnaround times (e.g., Orion)

Bottleneck Reduction

  • Fewer delays across lifecycle stages
  • Improved workflow throughput

Data Quality

  • Enhanced dataset quality
  • Improved dataset usability for AI, clinical, and regulatory applications

Stakeholder Alignment

  • Improved coordination across clinical, regulatory, and Data & AI teams

Work Model

Office-Based Role

  • Employees are expected to work in person at least 3 days per week.
  • Collaboration and stakeholder engagement are key aspects of the role.

Other Philips Work Models

  • Onsite Roles: Full-time presence at company facilities.
  • Field Roles: Work primarily at customer or supplier locations.

About Philips

Philips is a global health technology company dedicated to improving healthcare accessibility and outcomes worldwide. The company focuses on innovative technologies and solutions that enhance patient care, clinical workflows, and healthcare delivery.


Ideal Candidate Profile

The ideal candidate is a senior clinical professional with extensive experience in MRI, radiology, clinical research, and hospital engagement. They possess deep knowledge of healthcare data ecosystems, can effectively bridge clinical and technical teams, and have a proven ability to accelerate data acquisition programs while ensuring compliance, quality, and operational excellence in AI-driven healthcare environments.