Senior Specialist, Data Science

MSD Malaysia; Northern (KY); Hybrid; USD 129,000 - 203,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) retirement benefits

Paid holidays and vacation

Job summary

MSD Malaysia's Biologics Bio S&T PDSM organization seeks a Senior Specialist, Advanced Process Analytics & Data Strategy. This hands-on role applies data science, process modeling, and data architecture to strengthen biologics manufacturing analytics, collaborating with scientists, engineers, and digital teams.

You will develop, maintain, and improve analytics solutions, support process standardization, and help drive CPV, digital twins, and AI-enabled manufacturing data products in a

Qualifications

• B.S. or higher in a related engineering or life science field with 5+ years biopharma experience.
• Hands-on experience with Python or R for data analysis in manufacturing datasets.
• Experience with GMP/GxP, CPV, and data governance practices.
• Ability to translate manufacturing needs into data requirements and analytical solutions.

Responsibilities

• Develop and execute process analytics linking unit operations to QA attributes.
• Build data flow maps across MES, LIMS, PI Historian, SAP, and ELN.
• Create dashboards and models for CPV, digital twins, and AI/ML workflows.
• Collaborate with IT, SMEs, and external partners to ensure data quality and governance.
• Support data standardization and cross-site reuse of manufacturing data.

Skills

Bioprocess Engineering

Data Science

Python

R

SQL

Process Analytics

CPV

GxP

Root Cause Analysis

Education

B.S. in Chemical Engineering, Biochemical Engineering, Bioengineering, Life Sciences

M.S. in same fields with 3+ years of relevant experience

Ph.D. with 1+ year of relevant experience

Tools

OSIsoft PI/PI AF

Seeq

Power BI

Spotfire

Dataiku

JMP

AWS

Databricks

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

1. B.S. in Chemical Engineering, Biochemical Engineering, Bioengineering, Life Sciences, or a related field with 5+ years of relevant biopharmaceutical experience.
2. 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.

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 Management

Salary and Benefits

The salary range for this role is $129,000.00 - $203,100.00. 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.

Location and Work Arrangement

Hybrid Shift: 1st - Day

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.

Equal Employment Opportunity and Diversity

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: EEOC Know Your Rights EEOC GINA Supplement. 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. Learn more about your rights, including under California, Colorado and other US State Acts.