Associate Director, AI Solutions Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and develop innovative AI solutions, applications, and use cases.

• Conduct research to evaluate the feasibility of AI solutions.

• Offer architectural and design advice on AI, data science, processes, and workflows.

• Implement cutting-edge AI solutions for Research & Development and Corporate Functions.

• Create multi-agent orchestration, generative AI applications, and reusable AI solution capabilities.

• Stay updated with advancing AI technologies and guide their implementation across projects and teams.

• Collaborate with Data Science, AI Scientists, AI engineers, IT, and life sciences experts to design, develop, and implement robust AI solutions.

• Develop visions and roadmaps for AI products that align with business goals, technology, and market trends.

• Utilize data analysis and KPIs to track product performance and assess the business value of AI models.

• Construct AI solutions that adhere to responsible AI principles, 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 utilizing perception, planning, reasoning, orchestration, execution, and reflection loops.

• Oversee the lifecycle management and revisions of AI, ML, LLM, and agents in production.

• Provide guidance on AI ecosystem capabilities, platforms, frameworks, architecture, and new capability development.

• Mentor developers and oversee AI concepts and implementations.

• Lead or support AI/ML use case reviews, offering subject-matter expertise and execution assistance.

• Identify and resolve challenges during the 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 composed of technical, semi-technical, and business stakeholders.

• Manage stakeholder relationships by effectively communicating AI progress, results, impact, limitations, risks, and expectations.

• Act as a translator between technical AI teams and non-technical business stakeholders.

• Spearhead AI technology adoption and change management initiatives.

• Collaborate with internal functional areas and external partners to cultivate AI/ML capabilities.

• Work closely with data scientists, IT, cloud architects, and platform teams to ensure solutions are aligned with enterprise architecture and compliance.

• Partner with legal, privacy, and ethics teams to address algorithmic bias, fairness, transparency, and data privacy issues.

• Adapt to cycles of experimentation and iteration in AI product development.

• Concentrate on intelligence and context that drive product evolution.

⛳️ Requirements

• Master's degree in Data Science, Computer Engineering, Computer Science, Physics, Statistics, Information Systems, or a related field with a focus on advanced and modern Data Science, AI, and machine learning.

• PhD preferred.

• In-depth knowledge of real-world data assets and their use for generating scientific evidence and enhancing operational efficiency.

• Profound expertise in data engineering, data representation, generative AI, artificial intelligence, and machine learning techniques.

• Proven experience in architecting and delivering AI/ML use cases.

• Background in software/product engineering.

• Comprehensive understanding of AI and machine learning applications within the pharmaceutical industry.

• Familiarity with platforms such as Dataiku Data Science Studio, AWS SageMaker, Snowflake, or other data science tools.

• Experience with machine learning and AI technologies, including their integration with data engineering pipelines.

• Strong grasp of the Software Development Life Cycle (SDLC) and data science development lifecycle (CRISP).

• Experience in AI/ML-based software/product engineering.

• Knowledge of test and validation principles along with GxP validation.

• Proven experience in architecting, building, and maintaining large-scale data and AI solutions in scientific, regulated, or research-intensive environments.

• Significant experience in the pharmaceutical, biotech, or life sciences industry, particularly in drug development, clinical trials, or R&D, is highly desirable.

• Demonstrated success in 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 datasets related to claims, clinical trials, regulatory, quality, and other life sciences operations.

• Awareness of data collection, governance, and structuring challenges for improved AI outcomes.

• Strong collaboration and project management skills across internal and cross-functional teams.

• Excellent communication and stakeholder management abilities.

• Highly self-motivated, capable of working independently as well as collaboratively.

• Creative problem-solving skills utilizing responsible AI and other technologies.

🏝️ Benefits

• Comprehensive medical, dental, vision, and prescription drug coverage.

• Basic life insurance provided by the company.

• Accidental death and dismemberment insurance.

• Short-term and long-term disability insurance.

• Tuition reimbursement.

• Assistance with student loans.

• Generous matching for 401(k).

• Flexible time off options.

• Paid holidays.

• Paid leave programs.

• Additional benefits provided by the company.

• Opportunity for incentives.