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Johnson & Johnson
Johnson & Johnson
H1B वीज़ा प्रायोजकऔषधियाँजैव प्रौद्योगिकीस्वास्थ्य सेवा
Johnson & Johnson एक वैश्विक स्वास्थ्य सेवा कंपनी है, जो फार्मास्यूटिकल्स, चिकित्सा उपकरणों और उपभोक्ता स्वास्थ्य के क्षेत्र में काम करती है। इसके अनुसंधान और उत्पाद विकास कार्यों में ऑन्कोलॉजी, इम्यूनोलॉजी, न्यूरोसाइंस और हृदय-फुफ्फुसीय स्थितियों के लिए दवाएं और उपचार शामिल हैं। साथ ही, कंपनी हृदय संबंधी देखभाल, ऑर्थोपेडिक्स, सर्जरी और दृष्टि के लिए MedTech समाधान भी विकसित करती है। इसके व्यापक कार्यों में स्वास्थ्य और कल्याण शिक्षा, बड़े पैमाने पर विनिर्माण, निवेशक गतिविधियां और वैश्विक सामाजिक प्रभाव की पहल भी शामिल हैं, जिससे वैज्ञानिक, नैदानिक, इंजीनियरिंग, विनिर्माण, वाणिज्यिक और कॉर्पोरेट कार्यों में अवसर बनते हैं।
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कंपनी की नौकरियाँ

Principal Scientist, Data Science and Scientific Data Products

Lead development of AI-ready scientific data products for Johnson & Johnson’s drug discovery and development work. The role spans AWS integration, predictive modeling, metadata, and scientific data architecture.

USसंयुक्त राज्यNJन्यू जर्सीPAपेंसिल्वेनिया
$1,17,000 – $2,01,250 / वर्ष
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AWSक्लाउड

विवरण

  • Lead the design and evolution of scientific data products and integration strategies for AI-enabled drug discovery and development.
  • Build interoperable, AI-ready data products that connect discovery, preclinical, clinical, safety, and real-world evidence data.
  • Set data architecture, integration, metadata, and productization approaches for knowledge graphs, GraphRAG, semantic reasoning, advanced analytics, and agentic AI.
  • Direct data product strategy across discovery research, translational science, preclinical safety, clinical development, pharmacovigilance, and real-world evidence.
  • Create reusable data products for analytics, AI, knowledge graphs, and scientific reasoning.
  • Develop product roadmaps that support organizational priorities and scientific goals.
  • Design integration and harmonization frameworks for SEND, SDTM, ADaM, MedDRA, imaging, omics, biomarkers, pathology, and real-world data.
  • Plan implementation of scientific data products on AWS.
  • Work with Amazon engineering and platform teams to deliver scalable data pipelines and products.
  • Provide technical leadership and architectural guidance in line with Data Strategy recommendations.
  • Align digital solutions with enterprise architecture, security, governance, and AI-readiness needs.
  • Lead development of curated datasets, semantic-ready products, feature stores, metadata products, scientific data services, and AI-ready assets.
  • Set reusable methods for data onboarding, transformation, validation, and publication.
  • Define metadata standards and data quality frameworks.
  • Apply lineage, provenance, traceability, and FAIR data principles.
  • Set monitoring and quality controls for scientific data products.
  • Build predictive AI and machine learning models for translational safety decisions.
  • Collaborate with discovery, toxicology, clinical, safety, and data scientists, as well as Data Strategy partners, knowledge architects, and AI engineers.
  • Turn scientific questions into scalable data products and technical solutions.

आवश्यकताएँ

  • Master’s or doctoral degree in computer science, data engineering, bioinformatics, biomedical informatics, information systems, computational biology, or a related scientific field.
  • At least five years of experience in scientific data engineering, data architecture, data products, or life sciences informatics.
  • Proven experience designing and delivering scientific data products at enterprise scale.
  • Experience supporting drug discovery, development, clinical research, or pharmacovigilance organizations.
  • Experience developing predictive models for drug discovery, development, clinical research, or pharmacovigilance organizations.
  • Strong skills in data architecture and modeling, data product design, cloud-native platforms, metadata management, data governance, and predictive modeling.
  • Experience with AWS data platforms, data lakes and lakehouses, distributed processing, APIs and data services, and data cataloging and lineage tools.
  • Strong familiarity with SEND, SDTM, ADaM, and MedDRA.
  • Familiarity with FHIR, OMOP, DICOM, and biomarker and omics data standards is preferred.
  • Experience with knowledge graphs, semantic architectures, or GraphRAG initiatives is preferred.
  • Experience building AI-ready data products and feature stores is preferred.
  • Familiarity with ontology-based data integration approaches.
  • Experience working with cloud providers or external platform teams.
  • Experience in highly regulated scientific settings.
  • Strategic thinking and ability to shape long-term data product roadmaps.
  • Ability to connect scientific and technical teams and influence cross-functional groups without direct authority.
  • Strong execution skills and a focus on scalable, reusable solutions.

लाभ

  • Pension retirement plan.
  • 401(k) savings plan.
  • Long-term incentive program.
  • 120 hours of vacation per calendar year.
  • 40 hours of sick time per calendar year; 48 hours for Colorado residents and 56 hours for Washington residents.
  • Holiday pay, including 13 floating holidays per calendar year.
  • Up to 40 hours of work, personal, and family time per calendar year.
  • 480 hours of parental leave within one year of a child’s birth, adoption, or foster placement.
  • Bereavement leave: 240 hours for an immediate family member or 40 hours for an extended family member per calendar year.
  • Caregiver leave: 80 hours in a rolling 52-week period; the source also lists 10 days.
  • 32 hours of volunteer leave per calendar year.
  • 80 hours of military spouse time off per calendar year.
  • Accommodations during the interview process.
  • Hybrid work arrangement.

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