Associate Director, AI Solutions Scientist

Otsuka Pharmaceutical Companies (U.S.)

. Architect and develop modern AI solutions, use cases, and applications .

Posted 10/9/2026full-timeRemote • United StatesSenior💰 $169,222 - $253,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in architecting and developing AI solutions, with a strong focus on generative AI, machine learning, and data science applications in regulated environments. Proven ability to lead cross-functional teams, manage stakeholders, and ensure compliance with industry standards while driving innovation in AI technologies.

Highest-signal resume keywords

AI Solution ArchitectureGenerative AI ApplicationsData Science PlatformsPharmaceutical Industry ExperienceStakeholder Management

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine Learning TechniquesData EngineeringAI/ML Use Case DevelopmentSoftware Development Life Cycle (SDLC)Data AnalysisAI Model EvaluationData GovernanceAI/ML IntegrationGxP ValidationData Representation

Soft Skills

Project ManagementCreative Problem SolvingCollaborationCommunicationAdaptability

Tools & Technologies

Dataiku Data Science StudioAWS SageMakerSnowflakeAI Ecosystem PlatformsData Analytics Tools

Industry Keywords

Life SciencesPharmaClinical TrialsDrug DevelopmentRegulatory Compliance

Tech Stack

Tools & technologies

AWSCloudSDLC

About the role

Key responsibilities & impact

Architect and develop modern AI solutions, use cases, and applications
Conduct research to assess AI solution feasibility
Provide architectural and design guidance on AI, data science, processes, and workflows
Implement state-of-the-art AI solutions for R&D and Corporate Functions
Develop multi-agent orchestration, generative AI applications, and reusable AI solution capabilities
Keep current with evolving AI technologies and guide implementation across projects and teams
Design, develop, and implement robust AI solutions with Data Science, AI Scientists, AI engineers, IT, and life sciences subject matter experts
Develop AI product visions and roadmaps aligned with business objectives, technology, and market trends
Use data analysis and KPIs to monitor product performance and evaluate AI model business value
Build AI solutions aligned with responsible AI, privacy by design, and regulatory compliance
Experiment with, develop, train, fine-tune, validate, and evaluate AI/ML models
Design, implement, and deploy agentic AI systems using perception, planning, reasoning, orchestration, execution, and reflection loops
Oversee AI, ML, LLM, and agent lifecycle management and revisions in production
Guide AI ecosystem capabilities, platforms, frameworks, architecture, and new capability development
Guide developers and provide oversight on AI concepts and implementation
Lead or assist with AI/ML use case reviews and provide subject-matter expertise and execution support
Identify and resolve issues during development and production support of data analytics and AI applications
Develop and promote reusable data and AI components across business functions and the AI ecosystem
Lead cross-functional teams involving technical, semi-technical, and business stakeholders
Manage stakeholders by communicating AI progress, outcomes, impact, limitations, risks, and expectations
Translate between technical AI teams and non-technical business stakeholders
Lead AI technology adoption and change-management efforts
Partner with internal functional areas and external partners to develop AI/ML capabilities
Collaborate with data scientists, IT, cloud architects, and platform teams to align solutions with enterprise architecture and compliance
Collaborate with legal, privacy, and ethics teams on algorithmic bias, fairness, transparency, and data privacy
Adapt to experimentation and iteration cycles in AI product development
Focus on intelligence and context that drive product evolution

Requirements

What you’ll need

Master's degree in Data Science, Computer Engineering, Computer Science, Physics, Statistics, Information Systems, or a related discipline focused on advanced and modern Data Science, AI, and machine learning
PhD preferred
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, artificial intelligence, and machine learning techniques
Experience architecting and delivering AI/ML use cases
Experience in software/product engineering
Deep understanding of AI and machine learning and its applications in Pharma
Experience with Dataiku Data Science Studio, AWS SageMaker, Snowflake, or other data science platforms
Experience 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)
Experience in AI/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 scientific, regulated, or research-heavy environments
Strong experience in pharmaceutical, biotech, or life sciences industry, particularly drug development, clinical trials, or R&D, highly desirable
Proven track record implementing and deploying proof-of-concept and production-grade generative AI, AI/ML, and large language model applications
Understanding of life sciences R&D business processes
Experience with claims, clinical trial, regulatory, quality, and other life sciences operations datasets
Understanding of data collection, governance, and structuring problems for better AI outcomes
Strong internal and cross-functional collaboration and project management skills
Excellent communication and stakeholder management skills
Highly self-motivated and able to work independently and collaboratively
Creative problem solving using responsible AI and other technologies

Benefits

Comp & perks

Comprehensive medical, dental, vision, and prescription drug coverage
Company-provided basic life insurance
Accidental death and 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
Incentive opportunity