- Salary
- $129k – $203k
- Location
- USA - Pennsylvania - West Point, United States of America
- Workplace
- Hybrid
- Type
- Full-time
- Department
- IT
- Seniority
- Senior
- Education
- PhD
- Closing date
- Today
- Source
- Workday
Description
Job Description
About the Organization
The Biologics Science and Technology Platforms, Data, Modeling, and Statistics (PDSM) organization is a highly technical, science-forward function embedded within Bio S&T. We partner closely with manufacturing sites, IT, and process engineers to deliver data-driven process insights, statistical modeling, and digital capabilities that accelerate biologics commercialization and manufacturing excellence.
Our mission is to bridge the gap between traditional process engineering and modern data science. We build the foundational architectures, digital workflows, and analytical models that underpin every initiative across the biologics network—enabling proactive process monitoring (PPM), continued process verification (CPV), yield optimization, tech transfer, and AI-ready manufacturing.
We work hand-in-hand with our IT and manufacturing partners to co-design process analytics platforms. Our team contributes deep bioprocessing domain understanding paired with technical data science capabilities, ensuring the right process parameters and quality attributes are captured, contextualized, and modeled to drive real operational outcomes.
Position Summary
The Senior Specialist, Advanced Process Analytics & Data Strategy is a technical individual contributor role within PDSM. The primary expectation is hands-on execution and support, applying data science, process modeling, and data architecture concepts to strengthen biologics manufacturing analytics. The successful candidate will use their bioprocess engineering background to develop, maintain, and improve analytics solutions, support process standardization, and collaborate closely with scientists, engineers, and digital teams.
We are seeking candidates who fit the Domain-to-Data Professional profile:
- A bioprocess, biochemical, or regulated manufacturing engineer who has developed meaningful data science expertise through hands-on work with process, analytical, and batch data. You must be able to apply tools such as Python, R, SQL, and statistical modeling to support process characterization, digital analytics, root-cause investigations, and regulatory-ready manufacturing data products.
Key Responsibilities
1. Biologics Process Analytics & Engineering Support
- Support the development and execution of process analytics activities that connect unit operations, process parameters, and quality attributes through structured manufacturing data models.
- Translate bioprocessing and manufacturing needs into clear data requirements and help convert available data capabilities into practical scientific and operational insights.
- Contribute to process-focused data initiatives by performing analysis, developing datasets and visualizations, documenting requirements, and coordinating with engineers, scientists, and IT partners.
2. Manufacturing Data Architecture & Contextualization
- Build and maintain a clear data flow map across the biologics manufacturing network, integrating core manufacturing systems (MES, LIMS, PI Historian, SAP, ELN).
- Support process data contextualization and ontology mapping by helping link raw process and analytical data across unit operations, sites, and product lifecycle stages.
- Collaborate with IT and data engineering partners to support scalable, GxP-compliant data solutions by providing bioprocess domain context, data validation, and user requirements.
- Support data integrity expectations by applying ALCOA+ principles during data review, validation, documentation, and routine use of manufacturing data products.
3. Process Monitoring, Modeling & Statistical Enablement
- Develop and deploy fit-for-purpose dashboards, process visualizations, and analytics to enable Proactive Process Monitoring (PPM), trend identification, and rapid root-cause investigation support.Work with Statistical Sciences and Process/Product Modeling teams to prepare, structure, and validate datasets that support CPV, digital twins, AI/ML models, and multivariate analysis.
- Collaborate with internal manufacturing sites and Contract Manufacturing Organizations (CMOs) to establish sustainable data access and improve the usability of process/analytical data for technical troubleshooting.
4. Process Governance & Standardization Support
- Apply established process data standards, nomenclature, and ownership models to support cross-site comparability and reliable reuse of manufacturing data.
- Participate in data stewardship activities by maintaining documentation, identifying data quality issues, and supporting routine governance practices with engineering and science teams.
5. Stakeholder Engagement & Capability Building
- Collaborate with Technical Product Managers, process SMEs, Quality, Regulatory Affairs, and IT to support shared process-analytics priorities and deliverables.
- Support digital and data literacy across Bio S&T by preparing templates, job aids, training materials, and examples that help users apply governed self-service analytics appropriately.
Education Requirements
- B.S. in Chemical Engineering, Biochemical Engineering, Bioengineering, Life Sciences, or a related field with 5+ years of relevant biopharmaceutical experience.
- M.S. in the same fields with 3+ years of relevant experience, or Ph.D. with 1+ years of relevant experience.
Required Experience and Skills
Bioprocess Engineering & Domain Expertise
- Strong foundational knowledge of biologics manufacturing (Upstream/Downstream
- Proven experience utilizing process data (PI Historian, MES, LIMS) to troubleshoot manufacturing issues, monitor process performance, or support regulatory filings.
- Deep understanding of GMP/GxP environments, Continued Process Verification (CPV), and quality/compliance requirements in biomanufacturing.
Data Science & Technical Engineering
- Hands-on experience with Python or R for data manipulation, statistical analysis, and scripting—applied specifically to scientific or manufacturing datasets.
- Moderate to strong hands-on SQL skills; ability to query, transform, and validate data across relational databases.
- Understanding of how to extract and structure time-series data (e.g., from PI/DeltaV) and relational batch data to build actionable process models.
- Familiarity with data architecture concepts (data lakes, data warehousing) and experience collaborating with IT/Data Engineering to operationalize analytical pipelines.
Collaboration, Execution, and Communication
- Strong execution skills with the ability to translate defined priorities into clear workplans, analyses, documentation, and deliverables.
- Ability to work effectively across technical, business, Digital, Quality, and external partner stakeholders to gather input, resolve issues, and support aligned execution.
- Ability to support adoption of new data practices and tools by preparing clear instructions, examples, and user-facing support materials.
- Ability to translate complex technical and data concepts into clear, actionable recommendations for both technical and non-technical audiences.
- Comfortable working in evolving technical areas with guidance from functional leads and SMEs, including clarifying requirements and identifying practical next steps.
- Demonstrated ability to contribute as a reliable technical team member by sharing knowledge, documenting methods, and supporting peers through hands-on problem solving.
Preferred Experience and Skills
- Experience with biologics manufacturing data systems and the specific data challenges associated with bioprocess scale-up, tech transfer, and commercial manufacturing.
- Familiarity with data platform and mapping standards, OSIsoft PI / PI AF, Seeq, Power BI, Spotfire, Dataiku, JMP, AWS, Databricks.
- Experience preparing technical documentation, data dictionaries, mapping files, user requirements, or validation summaries for manufacturing data workflows.
- Background in PPM, CPV, investigation support analytics, cross-site process robustness analysis, or statistical process control in a GMP environment.
- Experience with external manufacturing data exchange — partnering with CMOs and external sites to establish governed data access and contextualization.
- Experience with master data management or semantic data models that support cross-system comparability and reuse.
Why Join PDSM
This is a rare opportunity to build something foundational. PDSM is in the early stages of creating a truly integrated data and digital capability for biologics commercialization — and the Data Strategy function is at the center of that work. You will:
- Shape the data architecture and governance framework that underpins Bio S&T’s entire digital and analytics agenda.
- Work at the intersection of pharmaceutical manufacturing science and cutting-edge data and digital capabilities.
- Partner with a high-performing, mission-driven team across PDSM, Digital, IT, and the broader Bio S&T organization.
- Contribute directly to accelerating how transformative medicines reach patients — faster, smarter, and with greater scientific confidence.
- Ability to travel up to 15%.
Required Skills:
Business Intelligence (BI), Data Access, Database Design, Data Engineering, Data Infrastructure, Data Integrity, Data Management, Data Mapping, Data Modeling, Data Reconciliation, Data Science, Data Standards, Data Structures, Master Data, Model Driven Design, SQL Databases, Stakeholder Relationship ManagementPreferred Skills:
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The salary range for this role is
$129,000.00 - $203,100.00This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.
The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.
We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days. More information about benefits is available at https://jobs.merck.com/us/en/compensation-and-benefits.
You can apply for this role through https://jobs.merck.com/us/en (or via the Workday Jobs Hub if you are a current employee). The application deadline for this position is stated on this posting.
San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance
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Employee Status:
RegularRelocation:
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NoTravel Requirements:
10%Flexible Work Arrangements:
HybridShift:
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n/aJob Posting End Date:
09/23/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.