Neural Nexus – Data Lead

Neural Nexus – Data Lead

Requirements

• Doctorate degree and 4 years of data architecture, analytics, AI/ML, or data strategy roles; commercial experience
• OR Master’s degree and 8 years of data architecture, analytics, AI/ML, or data strategy roles; commercial experience
• OR Bachelor’s degree and 10 years of data architecture, analytics, AI/ML, or data strategy roles; commercial experience
• At least 4 years experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation of resources.

Responsibilities

• Lead the overall Data strategy, infrastructures, and processes for the Neural Nexus platform.
• Define, articulate, and champion the strategic vision and long-term roadmap for the Neural Nexus data, infrastructure, and processes.
• Work closely with AI&D / Enterprise team to ensure compliance, integrity, accuracy, and reliability of all available internal and external data.
• Define and implement data governance framework and procedures for data ownership, lineage tracking, and stewardship.
• Develop AI-Readiness Infrastructure including frameworks to integrate structured and unstructured data into a unified data architecture.
• Implement automated NLP-driven pipelines to extract, normalize, and align entities and relationships across data types.
• Design and oversee the implementation of data and content tagging.
• Act as a key internal accelerator and educator for Generative AI, translating its complex capabilities into clear business value propositions.
• Lead and mentor cross-functional teams, fostering collaboration between business, IT, data science, and engineering.
• Cultivate a highly collaborative and inclusive environment that ensures seamless communication and execution throughout the Neural Nexus data and platform’s design, development, deployment, and operational phases.
• Develop and implement comprehensive strategies to drive broad and effective user adoption of Neural Nexus data and platform across the organization.
• Define, track, and rigorously report on relevant KPIs to measure platform impact and user engagement.
• Lead and champion change management initiatives associated with the introduction of NN and new automated processes.

Preferred Qualifications

• Extensive experience in Biotechnology/Pharmaceutical internal and external datasets, and consultative experience spanning across different data – Commercial and/or Medical, analytics fields, and therapeutic areas.
• Strong experience working directly with Business ie. Marketing, Sales, Medical, and/or Analytics Functions.
• Extensive understanding of data architecture, data management standard processes, and cloud computing platforms as they pertain to supporting AI/ML workloads.
• Demonstrated experience in management and integration of data solutions and processes.
• Demonstrated success in developing and operationalizing data foundations that support advanced analytics and AI/ML use cases.
• Passion for deriving data insights, storytelling, and driving measurable impact.
• Demonstrated flexibility and adaptability in a fast-paced, dynamic environment.
• Strong conceptual and practical understanding of AI/ML technologies, particularly Generative AI.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure), and modern data tools like Databricks, Snowflake, or BigQuery.
• Ability to assess data maturity and develop roadmaps for improving data readiness for AI use cases.
• Consistent track record of successfully leading large-scale, complex, cross-functional initiatives.
• Demonstrable experience in developing robust cases, creating strategic roadmaps, managing budgets, and allocating resources effectively.
• Strong commitment to maintaining the highest ethical standards in all analyses and business practices.
• Demonstrated success in leading organizational change management efforts and driving the adoption of new technologies and processes.
• Experience working effectively with international teams and diverse global partners.
• Superior ability to analyze complex, multifaceted problems and develop data-driven strategies.
• Strong, critical problem-solving capabilities characterized by a pragmatic, analytical, and results-oriented approach.
• Exceptional leadership capabilities with proven ability to inspire, motivate, and influence cross-functional teams.
• Outstanding verbal, written, and presentation skills.