Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
$117к-184к/год
$150к$170кмедиана$190к
По похожим ролям (49) ~ $170к/год
На СНГ рынке: $4.2к/мес ($3к - $5.9к)
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Отличная вакансия
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Понятная зона ответственности на стыке научного ПО и инженерии данных в крупной фармкомпании даёт возможность работать над промышленными решениями, хотя охват роли широкий, а требования к опыту высокие.
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Широкий охватСовременные технологииВлияние на наукуКрупная фармкомпания
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Specialist, Scientific Software Engineer, Digital Insights, DSCS Digital Technologies (Hybrid) (Scientific Software/Data Engineering): Building production-grade scientific software, backend services, APIs, data pipelines, and data products for drug development and laboratory automation with an accent on scaling prototypes, integrating scientific instruments, and maintaining reliable analytics-ready data. Focus on designing reusable platforms, modernizing fragmented tools, and deploying secure enterprise systems with scientists, IT, infrastructure, security, and data governance teams.
Location: Hybrid role available in Rahway, New Jersey; Boston, Massachusetts; Cambridge, Massachusetts; or West Point, Pennsylvania, United States.
Salary: $117,000–$184,200 base salary annually for the primary location; annual bonus and long-term incentive may also apply.
Company
hirify.global develops medicines and supports drug substance, drug product, analytical development, clinical supply, and related scientific operations through digital technologies.
What you will do
Build, scale, and sustain scientific and laboratory automation solutions from prototypes into secure, maintainable, enterprise-grade production software.
Design reusable platforms, backend services, and APIs that unify analytical instrument and laboratory data and consolidate legacy tools.
Develop and operate production data pipelines, data models, and reusable data products for reliable, analytics-ready data.
Own solution architecture, development, integration testing, documentation, deployment, user acceptance, and production support.
Partner with scientists, data scientists, IT, infrastructure, security, data governance, vendors, and other stakeholders to translate scientific needs into durable software.
Establish engineering practices including version control, code review, automated testing, CI/CD, onboarding, training, and production rollout.
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 plus at least 2 years of industrial, pharmaceutical, or relevant experience; or a B.S. plus at least 4 years of such experience.
Deep hands-on software development experience building production-grade applications, backend services, and APIs using Python and/or equivalent languages.
Experience scaling and hardening software from prototype to production, architecting reusable platforms, and modernizing or consolidating fragmented or legacy tools.
Experience partnering with IT, infrastructure, security, and/or data governance teams to deploy and sustain software within enterprise standards.
Strong data engineering experience designing, building, and operating production ETL/ELT pipelines, data models, and data products using databases, data warehouses, or data lakes.
Experience integrating software with scientific instruments, laboratory systems, or external platforms through APIs, SDKs, or file-based interfaces.
Experience with version control, automated testing, code review, and CI/CD.
Ability to translate complex scientific requirements into maintainable software and communicate technical concepts clearly to non-technical audiences.
Nice to have
Experience supporting pharmaceutical development, including drug substance, drug product, or analytical development.
Experience integrating analytical instrument software, chromatography data systems, laboratory informatics ecosystems, ELN/LIMS platforms, or Signals.
Experience with high-throughput screening, experimentation workflows, scientific data standards, FAIR data principles, standardized formats, and long-term archival.
Experience delivering scientific or laboratory data products and using data engineering tooling or orchestration frameworks.
Experience developing user-facing web applications for scientific data and workflows.
Familiarity with cloud platforms, containerization, data governance, data lineage, and validation frameworks in regulated GxP environments.
Prior cross-functional software deployments, user training, and production support experience.
Culture & Benefits
Hybrid work arrangement with approximately 10% travel.
Regular employee status with medical, dental, vision, insurance, retirement benefits including 401(k), paid holidays, vacation, and compassionate and sick days.
Inclusive, multidisciplinary, team-oriented environment focused on trusted partnerships, technical innovation, and collective problem-solving.
Visa sponsorship is available.
Domestic and international relocation is listed as available.
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