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Otsuka Pharmaceutical

Global pharma maker of Abilify

Associate Director, AI and Data Scientist

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timePrinceton, NJ, USAIn-person

About the Job

Requirements

  • A Master's degree in Data Science, Computer Engineering, Computer Science, Physics, Statistics, Information Systems, or a related discipline, with a focus on advanced and modern data science, including the use of artificial intelligence and machine learning.
  • Expertise in real-world data assets and using them to generate scientific evidence and guide operational effectiveness and efficiencies.
  • Deep expertise across data engineering, data representation, generative artificial intelligence, artificial intelligence and machine learning techniques, and experience architecting and delivering artificial intelligence and machine learning use cases.
  • Experience in artificial intelligence product development focused on artificial intelligence, data science, and machine learning, with a deep understanding of artificial intelligence and machine learning and their applications in pharmaceuticals.
  • Experience with data science and artificial intelligence enabling technology, such as Dataiku Data Science Studio, Snowflake, AWS SageMaker, or other data science platforms, and ability to maintain awareness as new artificial intelligence technologies emerge.
  • Ability to creatively solve problems using artificial intelligence and other technologies responsibly.
  • Ability to communicate complex technical concepts to non-technical audiences and manage stakeholders.
  • Familiarity with machine learning and artificial intelligence technologies and their integration with data engineering pipelines.
  • Strong understanding of the Software Development Life Cycle and data science development lifecycle (CRISP), including awareness of testing and validation approaches related to GxP and non-GxP.
  • Ability to deliver independently and collaborate with the team and broader ecosystem.
  • Experience in artificial intelligence and machine learning-based software or product engineering, familiarity with test and validation principles, and GxP validation.
  • Experience with data science enabling technology, such as Dataiku Data Science Studio, Snowflake, AWS SageMaker, or other data science platforms.
  • Experience architecting, building, and maintaining large-scale data and artificial intelligence solutions in a scientific, regulated, or research-heavy environment.
  • Experience implementing and deploying generative artificial intelligence and large language model applications in production environments.
  • Strong project management and cross-functional collaboration skills focused on delivering impactful initiatives.
  • Understanding of life sciences research and development business processes.
  • Experience working with relevant life sciences datasets such as claims, clinical trial data, regulatory data, quality data, and other life sciences operations datasets.
  • Experience implementing proofs of concept and production-grade artificial intelligence, machine learning, generative artificial intelligence, and large language model applications in production environments.
  • Understanding of data's role in artificial intelligence, including data collection, governance, and how to structure a problem for better artificial intelligence outcomes.

Responsibilities

  • Develop a product vision and roadmap for artificial intelligence-driven solutions, aligning artificial intelligence capabilities with business objectives, technology, and market trends; implement data science and artificial intelligence portfolio objectives and contribute to data and analytics strategies, especially for augmenting and accelerating research and development operations using artificial intelligence.
  • Experiment with, develop, train, or fine-tune artificial intelligence models for business problems and processes, validate and evaluate them for inclusion in broader solutions, and demonstrate a strong foundational understanding of artificial intelligence, machine learning, statistics, and data science concepts.
  • Investigate and conduct proof-of-concept initiatives and develop solutions for new artificial intelligence applications using large language models and generative artificial intelligence to enhance data analytics and accelerate candidates across drug development phases.
  • Use data analysis and key performance indicators to monitor product performance and make informed decisions, considering artificial intelligence model evaluation metrics and business value in pharmaceutical research and development operations and enterprise use cases.
  • Apply knowledge of drug development, clinical trials, and external healthcare data to build artificial intelligence solutions that conform to responsible artificial intelligence, privacy by design, and regulatory compliance requirements.
  • Deliver effective artificial intelligence-enabled products that build trust, drive adoption, and lead to transformation; use design-centric approaches grounded in user needs, processes, regulations, and responsible artificial intelligence.
  • Provide technical input on the artificial intelligence ecosystem, platforms, frameworks, and architecture, including solution evolution and new capability development; guide developers and technical team members and direct vendors, providing oversight on artificial intelligence concepts and implementation.
  • Stay current with industry trends and advancements in artificial intelligence, machine learning, research and development processes, and data; provide insights to team leadership on technical roadmaps and strategy, and apply innovative analytical solutions, tools, methodologies, and technologies.
  • Design, implement, and deploy agentic artificial intelligence systems using perception, planning, reasoning, orchestration, execution, and reflection loops.
  • Oversee the lifecycle management and revisions of artificial intelligence solutions, including machine learning models, large language models, and agents in production environments.
  • Lead efforts to support adoption of new artificial intelligence technologies and develop processes to optimize data and analytics systems and their execution, ensuring responsible use of emerging technologies.
  • Lead or assist in reviewing artificial intelligence and machine learning use cases to ensure artificial intelligence guidelines, frameworks, platform components, and responsible artificial intelligence are enabled; act as a subject matter expert on cross-functional teams, supporting data engineering needs and resolving issues during development and production support of data analytics and artificial intelligence applications.
  • Ensure development of reusable data and artificial intelligence solution components and promote their use across the data and artificial intelligence ecosystem and business functions, including clinical operations, asset management, quality, safety, regulatory, real-world data, and enterprise functions.
  • Collaborate with technical, semi-technical, and business stakeholders to lead and align diverse teams, including data scientists, engineers, designers, marketing, legal, and executives.
  • Guide and manage stakeholders by communicating artificial intelligence progress, outcomes, impact, limitations, and risks and managing expectations.
  • Bridge communication between technical artificial intelligence teams and non-technical business stakeholders.
  • Partner with internal functional areas and external partners to conceptualize, develop, or co-develop artificial intelligence and machine learning capabilities, leveraging artificial intelligence engineering, data engineering, artificial intelligence platform architecture, infrastructure, and information technology teams.
  • Collaborate with internal data and artificial intelligence scientists, information technology, and cloud architects to align data infrastructure and technical solutions with enterprise architecture and compliance needs; leverage existing team and organizational capabilities.
  • Collaborate with legal, privacy, and ethics teams to address algorithmic bias, fairness, transparency, and data privacy concerns.
  • Operate effectively amid ambiguity in artificial intelligence product development and adapt to continuous experimentation and iteration cycles.
  • Think beyond features and focus on curating intelligence and context that drives product evolution.

Desired Qualifications

  • Strong experience in the pharmaceutical, biotech, or life sciences industry, particularly in drug development and clinical trials.
  • Strong experience working within the pharmaceutical, biotech, or life sciences industry, particularly within research and development.

About the Company

Otsuka Pharmaceutical

Global pharma maker of Abilify

Otsuka Pharmaceutical develops and markets medicines and health products worldwide, including prescription drugs and nutraceutical beverages. Its product lineup ranges from pharmaceutical treatments such as Abilify (an antipsychotic) to consumer health drinks like Pocari Sweat, which helps replenish electrolytes. Abilify works as a psychiatric medication used to treat conditions such as schizophrenia and bipolar disorder, while Pocari Sweat is an ion-replacement beverage designed to restore minerals and fluids after activity or heat. The company differentiates itself through a long history dating back to its founding in 1921, a broad, globally scaled portfolio spanning drugs and health beverages, and a focus on health improvements across populations. Its stated goal is to create new products for better health worldwide.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Tokyo, Japan
Founded
1921

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