Senior Specialist, Scientific Software Engineer, Digital Insights, DSCS Digital Technologies (Hybrid)

MSD • Boston, MA

1d • $117,000 - $184,200 • Hybrid

About The Position

The Senior Specialist, Scientific Software Engineer will join the Digital Insights team within Development Sciences and Clinical Supply Digital Technologies. The role provides software and data engineering expertise to build, scale, and sustain scientific software, automation, and data solutions, moving scientist-built prototypes into secure, maintainable, production-grade capabilities. It works at the intersection of scientific software engineering, data engineering, and laboratory automation.

The successful candidate will own software and data engineering across the portfolio, designing reusable platforms, backend services, and APIs; developing reliable data pipelines and data products; and consolidating fragmented or legacy tools into enterprise-grade systems. The role works closely with scientists and partners across IT, infrastructure, security, data governance, and vendor teams to translate scientific needs into durable solutions that can be deployed and sustained in production.

Requirements

• Ph.D. in Computer Science, Data Science, Software Engineering, Chemistry, Physics, Engineering, Pharmaceutical Sciences, or a closely related field; or an M.S. in one of these fields with at least 2 years of industrial/pharmaceutical or relevant experience; or a B.S. in one of these fields with at least 4 years of industrial/pharmaceutical or relevant experience.
• Deep software development expertise, including hands-on experience building production-grade applications, backend services, and APIs using Python and/or equivalent languages.
• Demonstrated experience scaling and hardening software from prototype to production, including architecting reusable platforms and modernizing or consolidating legacy or fragmented tools.
• Experience partnering with IT, infrastructure, security, and/or data governance teams to deploy and sustain software in production within enterprise standards.
• Strong data engineering skills and demonstrated experience designing, building, and operating production ETL/ELT pipelines, data models, and data products, including working with databases, data warehouses, or data lakes.
• Experience developing software integrations with scientific instruments, laboratory systems, or external platforms through APIs, SDKs, or file-based interfaces.
• Experience with software engineering best practices, including version control such as Git, automated testing, code review, and CI/CD.
• Ability to translate complex scientific requirements into robust, maintainable software and communicate technical concepts clearly to non-technical audiences, with strong written and verbal communication skills.
• Ability to collaborate effectively in a dynamic, integrated, multidisciplinary, team-oriented environment.

Nice To Haves

• Experience supporting pharmaceutical development, such as drug substance, drug product, or analytical development, is strongly preferred.
• Hands-on experience integrating analytical instrument software and chromatography data systems, including building data-ingestion pipelines from instrument sources.
• Experience integrating with laboratory informatics ecosystems and ELN/LIMS platforms, such as Signals.
• Familiarity with high-throughput screening and experimentation workflows and the data they generate.
• Experience with scientific data standards and FAIR data principles, including standardized data formats and long-term data archival.
• Experience building and delivering data products in a scientific or laboratory context, and familiarity with data engineering tooling and orchestration frameworks.
• Experience developing user-facing web applications that surface scientific data and workflows.
• Familiarity with cloud platforms and containerization.
• Knowledge of data governance, data lineage, and validation frameworks in regulated environments such as GxP.
• Prior contributions to cross-functional software deployments, user training, and production support.

Responsibilities

• Provide software and data engineering expertise to build, scale, and sustain scientific and automation solutions, taking them from prototype to robust, secure, maintainable, enterprise-grade production software.
• Design and build reusable platforms, backend services, and APIs that unify analytical instrument and laboratory data, and consolidate fragmented or legacy tools into well-architected, scalable systems.
• Lead data engineering and data product development by designing and operating pipelines, data models, and reusable data products that keep data reliable, well-structured, and analytics-ready.
• Partner with IT, infrastructure, security, data governance, and vendor teams to deploy, integrate, and sustain production solutions while navigating enterprise standards and requirements.
• Own end-to-end software delivery, including solution architecture, development, integration testing, documentation, deployment, and user acceptance.
• Establish engineering best practices such as version control, code review, automated testing, and CI/CD.
• Collaborate with scientists, data scientists, and cross-functional stakeholders to translate scientific needs into durable software.
• Provide technical leadership during onboarding, training, and production rollout to reduce key-person dependencies.
• Demonstrate strong interpersonal, communication, and collaboration skills; model core values and foster a supportive culture; and contribute impactful technical innovation while building trusted partnerships across a multidisciplinary stakeholder network.

Benefits

• Medical, dental, and vision healthcare and other insurance benefits for employees and family
• Retirement benefits, including 401(k)
• Paid holidays
• Vacation
• Compassionate and sick days
• Eligible for annual bonus and long-term incentive, if applicable

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree