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Leader of R&D Digitalization & Advanced Analytics

Job in Melrose Park, Cook County, Illinois, 60161, USA
Listing for: 301044 Fresenius Kabi USA, LLC
Full Time position
Listed on 2026-06-19
Job specializations:
  • IT/Tech
    Data Analyst, AI Engineer (Applied/Software), Data Science Manager, Data Scientist
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Job Summary

The Head of R&D Digitalization & Advanced Analytics leads the end‑to‑end digital transformation of Global R&D, shaping the strategy and execution of digital, data, and automation initiatives across all R&D centers. This role is responsible for mapping scientific and operational processes, identifying opportunities to digitalize workflows, and enabling the effective use of data to accelerate development timelines, enhance decision‑making, and increase productivity.

A key mandate of the position is to convert scientific and operational data into predictive insights that support advanced modeling, simulation, and virtual experimentation (such as virtual labs) to drive faster, more robust formulation and drug product development. The role serves as a strategic integrator between science, data, and technology, partnering closely with R&D functions, IT, external collaborators, and senior leadership to embed digital capabilities into everyday R&D execution.

Salary

& Benefits

Salary Range: $,000. Eligible for an annual bonus plan with a target of 14% of the base salary.

Benefits offered include a 401(k) plan with company contributions, paid vacation, holiday and personal days, employee assistance program, and health benefits (medical, prescription drug, dental and vision coverage).

Responsibilities
  • R&D Digital Strategy & Roadmap – Develop and own the global R&D digitalization strategy aligned with R&D and BU Pharma objectives; map end‑to‑end R&D processes across all R&D centers (e.g., formulation, analytical, MS&T, feasibility, lifecycle) to identify automation and digitalization opportunities; prioritize initiatives based on scientific impact, speed, scalability, and return on investment.
  • Automation & Process Digitalization – Identify repetitive, manual, or data intensive R&D activities suitable for automation; drive implementation of automation solutions (e.g., data capture, workflow automation, integration of lab systems); establish global standards for digital tools and processes to ensure scalability and consistency across sites.
  • Advanced Analytics, Modeling & Virtual Development – Leverage R&D scientific data to build predictive models supporting formulation development, process optimization, and risk assessment; enable simulation‑based and data‑driven development approaches, including virtual labs and in silico experimentation, to reduce experimental cycles and accelerate decision making; partner with formulation, analytical, and MS&T experts to ensure models are scientifically sound and fit for purpose.
  • Data & Digital Enablement – Define R&D data architecture needs in collaboration with IT, ensuring accessibility, integrity, and regulatory compliance; promote reuse of scientific data across projects and lifecycle stages; embed digital tools into core R&D workflows rather than as standalone pilots.
  • Cross Functional Leadership & Change Management – Act as a change leader, driving adoption of digital tools and new ways of working across R&D sites; build strong partnerships with R&D leaders, IT, Quality, Regulatory, and external technology partners; develop digital and data capabilities within R&D through targeted upskilling and talent development.
  • Governance & Value Tracking – Establish clear governance for digital initiatives, including prioritization, milestones, and success metrics; track and communicate impact (e.g., cycle time reduction, cost avoidance, quality improvement, scientific insight generation); ensure digital investments deliver measurable business and scientific value.
Key Interfaces
  • Global R&D Leadership Team
  • Heads of Formulation, Analytical, MS&T, Feasibility, and Lifecycle Management
  • IT / Digital / Data Science teams
  • Quality and Regulatory
  • External technology and analytics partners
Equal Opportunity Statement

Fresenius Kabi is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, citizenship, immigration status, disabilities, or protected veteran status.

Employment at-Will

All employment is at‑will, meaning both the employee and Fresenius Kabi have the right to end the employment relationship at any time, in accordance with applicable federal and state laws.

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