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Amgen
Amgen
H1B vīzas sponsorsBiotehnoloģijaFarmaceitiskie produktiVeselības aprūpe
Amgen ir globāls biotehnoloģiju uzņēmums, kas izstrādā un komercializē no dzīvām šūnām ražotas zāles. Tā darbība ir vērsta uz smagām slimībām, tostarp slimībām ar ierobežotām ārstēšanas iespējām, un to atbalsta zinātniskie pētījumi un klīniskie izmēģinājumi. Uzņēmums ir saistīts ar sasniegumiem vēža ārstēšanā un aptaukošanās kontrolē, vienlaikus uzsverot ētisku pētniecību, pacientu drošību un vides ilgtspēju.
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Vakances uzņēmumā

Remote Data Scientist, Generative AI and Supply Chain at Amgen

Lead the development of generative AI, machine learning, and analytics capabilities for Amgen’s biotech supply chain. Guide solutions from experimentation through enterprise production.

USAmerikas Savienotās Valstis
103 852 $ – 140 505 $ / gads
AttālinātiPilna slodzeJaunākais speciālistsVidējais līmenisNepieciešamā Valoda: angļuDatu zinātnieks
MākonisPythonSQL

Apraksts

  • Lead technical data science work for assigned AI-enabled analytics capabilities.
  • Work with product owners and supply chain stakeholders to turn business needs into prioritized use cases, technical approaches, success measures, and delivery plans.
  • Build, assess, and improve generative and agentic AI solutions using large language models, retrieval-augmented generation, semantic search, prompt engineering, and multi-agent workflows.
  • Set up evaluation and monitoring for AI solutions, covering accuracy, relevance, robustness, safety, user feedback, and appropriate human review.
  • Use machine learning, statistical modeling, and time-series analysis for supply chain needs involving demand, supply, inventory, capacity, cost, risk, and operational performance.
  • Partner with data engineers to create trusted analytical datasets, reusable features, data quality checks, lineage, and documentation for AI and analytics products.
  • Integrate data science capabilities into enterprise applications with engineering, architecture, platform, testing, and delivery teams; support testing, deployment, production performance, and issue resolution.
  • Guide and review the work of data scientists, engineers, and delivery partners, coordinate dependencies, and encourage reusable approaches across related products.
  • Prepare technical documentation and operating procedures, and contribute to technical reviews.
  • Explain findings, tradeoffs, risks, recommendations, and business impact to technical and non-technical stakeholders; contribute to Agile delivery and applicable AI and data governance processes.

Prasības

  • Master's degree and 1 to 3 years of experience in computer science, IT, or a related field; or bachelor's degree in data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or a related field plus 2 years of relevant experience; or associate's degree in one of these fields plus 6 years of relevant experience.
  • Practical experience using Python and SQL for data analysis, feature engineering, machine learning, natural language processing, and AI solution development.
  • Experience designing or developing generative AI and large language model capabilities, such as AI assistants, retrieval-augmented generation, embeddings, semantic search, prompt engineering, or agentic workflows.
  • Strong grounding in machine learning, statistical analysis, exploratory data analysis, time-series methods, and model evaluation.
  • Experience taking data science or AI solutions from experimentation into production, including testing, version control, monitoring, and MLOps or LLMOps practices.
  • Ability to work with large, complex datasets and collaborate on data modeling, data quality, lineage, and reusable analytical data pipelines.
  • Ability to translate business problems into technical approaches, independently lead a technical workstream, and communicate results clearly.
  • Preferred: experience with supply chain, manufacturing, or biotech analytics, such as demand and supply planning, inventory, capacity, cost, financial planning, or operational KPIs.
  • Preferred: experience with cloud-based data and AI platforms, large-scale data processing, and integrating AI capabilities into enterprise applications.
  • Preferred: understanding of responsible AI, AI governance, security, compliance, observability, and ongoing solution performance management.
  • Preferred: experience supporting analytical or reporting products and collaborating with cross-functional teams and delivery partners in an Agile or SAFe environment.
  • Preferred: certification in data science, artificial intelligence, or machine learning.
  • Optional: cloud or data platform certification.
  • Excellent critical-thinking, analytical, and problem-solving abilities.
  • Strong communication, collaboration, and stakeholder-management abilities.
  • Ability to provide technical leadership and influence without formal authority.
  • Ability to connect technical work to business outcomes and explain complex topics clearly.
  • Strong presentation, knowledge-sharing, and mentoring abilities.

Priekšrocības

  • Comprehensive employee benefits, including a retirement and savings plan with generous company contributions.
  • Group medical, dental, and vision coverage.
  • Life and disability insurance.
  • Flexible spending accounts.
  • Discretionary annual bonus program.
  • Stock-based long-term incentives.
  • Award-winning time-off plans.
  • Flexible work models where possible.
  • Career development opportunities.
  • Financial plans with options to save for retirement and other goals.
  • Work-life balance support.

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