Senior Specialist, Data Science
Merck
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Job summary
Merck is seeking a Senior Specialist, Advanced Process Analytics & Data Strategy, to apply data science, process modeling, and data architecture to biologics manufacturing analytics. You will develop analytics solutions, support process standardization, and collaborate with scientists, engineers, and digital teams across sites.
The role emphasizes hands-on execution, data governance, and the creation of dashboards for proactive process monitoring, data visualization, and regulatory-ready
Qualifications
- Bachelor-level degree with strong data science experience in biopharma or regulated manufacturing.
- Proven ability to apply Python/R/SQL to process data, model processes, and support digital analytics.
- Experience with GMP/GxP environments and CPV/PPM concepts is preferred.
Responsibilities
- Biologics Process Analytics & Engineering Support
- Develop and execute process analytics activities linking unit operations, parameters, and quality attributes via data models.
- Translate process needs into data requirements and deliver actionable insights.
- Create datasets, visualizations, and documentation; coordinate with engineers, scientists, and IT.
- Build and maintain data flow maps across MES, LIMS, PI Historian, SAP, ELN.
- Support data contextualization and ontology mapping across sites and product lifecycle stages.
- Collaborate with IT/Data Engineering to operationalize analytical pipelines and ensure data governance.
- Apply ALCOA+ principles during data review, validation, and use of manufacturing data products.
- Develop dashboards and analytics to enable Proactive Process Monitoring and CPV/digital twin initiatives.
- Partner with CMOs and internal sites to improve data access and troubleshooting usability.
Skills
Education
Tools
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.
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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%.
- 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 Management
Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.
As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics. As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:
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We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.
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$129,000.00 - $203,100.00
This 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.
The application deadline for this position is stated on this posting.
We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
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
Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.
Regular
Domestic
No
10%
Hybrid
1st - Day
No
n/a
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.
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