Associate Director, AI and Data Scientist

Otsuka Pharmaceutical Companies (U.S.)

. Develop AI product visions and roadmaps aligned with business objectives, technology, and market trends .

Posted 10/7/2026full-timeRemote • New Jersey • United StatesSenior💰 $169,222 - $253,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing AI solutions within the pharmaceutical and life sciences sectors, focusing on data science, machine learning, and generative AI applications. Proven ability to lead cross-functional teams, manage AI product lifecycles, and ensure compliance with industry standards.

Highest-signal resume keywords

AI Product DevelopmentGenerative AI ApplicationsData Science PlatformsPharmaceutical R&D ExperienceStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning TechniquesData EngineeringAI/ML Use Case ArchitectureData AnalysisMLOpsLLMOpsPrompt EngineeringStatistical AnalysisSoftware Development Life Cycle (SDLC)Testing and Validation Principles

Soft Skills

Communication SkillsProject ManagementCross-Functional CollaborationChange ManagementAdaptability

Tools & Technologies

Dataiku Data Science StudioSnowflakeAWS SageMakerAI EcosystemsData Analytics Tools

Industry Keywords

Pharma R&DClinical TrialsDrug DevelopmentGxP ComplianceAlgorithmic Bias

Tech Stack

Tools & technologies

AWSSDLC

About the role

Key responsibilities & impact

Develop AI product visions and roadmaps aligned with business objectives, technology, and market trends
Implement Data Science and AI portfolio objectives and contribute to data and analytics strategies for R&D Operations
Experiment with, develop, train, fine-tune, validate, and evaluate AI/ML models for business problems
Develop and field enterprise AI systems using prompt engineering, embeddings, fine-tuning, LLMs, and generative AI
Conduct proof-of-concept initiatives and develop AI applications to enhance data analytics and accelerate drug development
Use data analysis and KPIs to monitor product performance and guide data-driven decisions
Develop AI solutions using Pharma R&D, drug development, clinical trial, and external healthcare data
Design user-centric AI-enabled products that build trust, drive adoption, and support transformation
Provide technical input on AI ecosystems, platforms, frameworks, architectures, and new capabilities
Guide developers, technical team members, and vendors on AI concepts and implementation
Design, implement, and deploy agentic AI systems using perception, planning, reasoning, orchestration, execution, and reflection loops
Oversee lifecycle management and revisions of AI solutions using MLOps and LLMOps processes and tools
Lead AI technology adoption, enablement, change management, and responsible use processes
Review AI/ML use cases for compliance with guidelines, frameworks, platform components, and responsible AI requirements
Develop reusable data and AI solution components and promote scalable reuse across business functions
Lead cross-functional teams of technical, semi-technical, and business stakeholders
Communicate AI progress, outcomes, impact, limitations, and risks to stakeholders
Partner with internal functional areas and external partners to conceptualize, develop, and co-develop AI/ML capabilities
Collaborate with legal, privacy, and ethics teams on algorithmic bias, fairness, transparency, and data privacy
Adapt to experimentation and iteration cycles while managing ambiguity in AI product development

Requirements

What you’ll need

Master's degree in Data Science, Computer Engineering, Computer Science, Physics, Statistics, Information Systems, or a related discipline with focus on advanced and modern Data Science, including AI 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 AI, AI, and machine learning techniques
Experience architecting and delivering AI/ML use cases
Experience in AI product development using AI, Data Science, and Machine Learning
Deep understanding of AI and Machine Learning and their applications in Pharma
Experience with Dataiku Data Science Studio, Snowflake, AWS SageMaker, or other data science platforms
Familiarity with machine learning and AI technologies and their integration with data engineering pipelines
Strong understanding of Software Development Life Cycle (SDLC) and data science development lifecycle (CRISP)
Awareness of testing and validation approaches related to GxP and non-GxP
Experience in AI and ML-based software/product engineering
Familiarity with test and validation principles and GxP validation
Experience architecting, building, and maintaining large-scale data and AI solutions in a scientific, regulated, or research-heavy environment
Strong experience within the pharmaceutical, biotech, or life sciences industry, particularly in drug development, clinical trials, or R&D, highly desirable
Proven track record implementing and deploying generative AI and large language model applications in production environments
Experience working with claims, clinical trial, regulatory, quality, and other life sciences operations datasets
Proven track record implementing proof-of-concept and production-grade AI/ML, generative AI, and LLM applications
Understanding of data collection, governance, and structuring problems for better AI outcomes
Excellent communication and stakeholder management skills
Strong internal and cross-functional collaboration and project management skills

Benefits

Comp & perks

Incentive opportunity
Comprehensive medical, dental, vision, and prescription drug coverage
Company-provided basic life insurance
Accidental death & dismemberment insurance
Short-term and long-term disability insurance
Tuition reimbursement
Student loan assistance
Generous 401(k) match
Flexible time off
Paid holidays
Paid leave programs
Other company-provided benefits