Neural Nexus - Data Lead

About the Role

Key Responsibilities

• Lead the overall Data strategy, infrastructures, and processes for the Neural Nexus (NN) - Generative AI and Automation platform.
• Work closely with Technology and AI&D organization to drive and deliver the design, implementation, rollout, and continuous evolution of the Neural Nexus program, ensuring alignment with cross-functional teams and enterprise priorities.
• Develop and articulate the strategic vision and long-term roadmap for Neural Nexus data, infrastructure, and processes.
• Ensure compliance, integrity, accuracy, and reliability of all data used in the commercialization of brands, providing strategic direction on data sources and acquisition strategies.
• Define and implement data governance frameworks, including data ownership, lineage tracking, and stewardship.
• Assess and develop data processes such as QC, Master Data Management, and Affiliation to ensure high standards of quality.
• Develop AI-Readiness Infrastructure, including frameworks to integrate structured and unstructured data, and implement automated NLP-driven pipelines.
• Design and oversee data and content tagging, collaborating with SMEs to maintain relevant taxonomies.
• Define role-based access modules to ensure data security and appropriate access.
• Act as an internal educator and advocate for Generative AI, translating its capabilities into business value and building organizational consensus.
• Lead and mentor cross-functional teams, fostering collaboration between business, IT, data science, and engineering.
• Cultivate a collaborative environment that facilitates communication and execution across the Neural Nexus platform lifecycle.
• Serve as a liaison between technical AI teams and pharmaceutical domain experts to ensure mutual understanding.
• Develop and implement strategies to drive user adoption of Neural Nexus, including partnering with training and change management teams.
• Define, track, and report KPIs to measure platform impact and user engagement.
• Lead change management initiatives and foster a culture of continuous learning and adaptation.

Requirements

• Doctorate degree and 4 years of experience in data architecture, analytics, AI/ML, or data strategy roles with commercial experience.
• OR Master's degree and 8 years of relevant experience.
• OR Bachelor's degree and 10 years of relevant experience.
• At least 4 years of experience managing people, leading teams, projects, or programs.
• Strong understanding of data architecture, data management, and cloud platforms supporting AI/ML workloads.
• Experience with data governance, data integration, and data quality processes.
• Knowledge of AI/ML workflows, especially Generative AI and model development lifecycles.
• Familiarity with cloud platforms such as AWS, GCP, Azure, and data tools like Databricks, Snowflake, or BigQuery.
• Proven ability to lead large-scale, complex initiatives and manage cross-functional teams.
• Excellent communication skills, with the ability to translate technical concepts for diverse audiences.
• Strong strategic and analytical thinking, problem-solving, and decision-making skills.
• Demonstrated leadership and influence in organizational change efforts.

Nice to Have

• Extensive experience with Biotechnology/Pharmaceutical datasets and consultative experience across data, analytics, and therapeutic areas.
• Experience working directly with Business functions such as Marketing, Sales, Medical, and Analytics.
• Deep understanding of data architecture, data management standards, and cloud computing platforms supporting AI/ML.
• Experience developing data foundations like data governance, architecture, and integration for AI/ML use cases.
• Passion for deriving insights, storytelling, and measurable impact.
• Adaptability and agility in fast-paced environments.
• Knowledge of AI/ML workflows, foundational data assets, and their impact on model performance.
• Experience with international teams and global partners.
• Strong project and program management skills, including risk management and resource allocation.
• Deep business acumen within the pharmaceutical industry.

Qualifications

• Doctorate, Master's, or Bachelor's degree with relevant experience as specified.
• Experience managing teams or leading projects in data architecture, AI/ML, or data strategy roles.

Benefits & Perks

• Comprehensive employee benefits package including health and welfare plans, retirement and savings plans with company contributions, medical, dental, and vision coverage, life and disability insurance, and flexible spending accounts.
• Discretionary annual bonus or sales-based incentive plan.
• Stock-based long-term incentives.
• Award-winning time-off plans.
• Flexible work models, including remote and hybrid arrangements.