# LumaBio Partners — Head of Enterprise AI & Data Science

- Generated: 2026-09-02 09:34:05 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4462153858/
- Provider: linkedin
- Posting time: approximately 2026-09-02 07:34 AM EDT (estimated from provider's '2 hours ago' at capture)
- Applicants: Be among the first 25 applicants
- Work model/location: Boston, MA; acceptable whether on-site or hybrid.; provider location: Boston, MA
- Compensation: Not disclosed; Head is not among Keith's compensation-waiver titles, so compensation cannot be verified.
- Travel: Not disclosed.
- Positioning track: Executive Leader
- Fit outcome: FAIL — 76.5%

## Direct-match strengths

Enterprise AI leadership, production delivery, governance, AWS, and substantial life-sciences/pharma credibility.

## Hard or material gaps

Hard compensation-verification failure; required Azure, PyTorch, and scikit-learn experience is unsupported.

## Evidence map

1. Enterprise AI strategy/governance (w3/e3): Direct IDW, MassMutual, AWS, and NorthBay evidence.
2. AI lifecycle through production (w3/e3): Multiple production AI, SaaS, and cloud platforms.
3. Multidisciplinary AI/data leadership (w3/e3): Led AI, ML, data, analytics, full-stack, and cloud teams.
4. ML/DL/NLP/GenAI/agents (w3/e2): Strong ML, TensorFlow, LLM, and agent evidence; less current framework breadth.
5. PyTorch/scikit-learn/MLflow (w3/e1): MLflow supported; PyTorch and scikit-learn unsupported.
6. Python/SQL/R (w2/e3): Python and SQL directly supported; disjunctive requirement met.
7. AWS and Azure (w3/e1): Deep AWS; no source-supported Azure experience.
8. Data/AI platform stack (w2/e2): Databricks, Bedrock, S3, and Glue supported; no Azure OpenAI/OpenSearch.
9. MLOps/governance/monitoring (w3/e3): SageMaker transparency, bias/drift, Responsible AI, and privacy governance.
10. Global matrix/pharma-health (w2/e2): Strong life-sciences/pharma and enterprise stakeholder work; global matrix leadership less explicit.

## Full normalized job description

We are partnering with a
global pharmaceutical organisation
that is making a significant investment in its enterprise Data & AI capabilities.
As part of this continued investment, they are looking to appoint a
Head of Enterprise AI & Data Science
to provide strategic and technical leadership across Artificial Intelligence, Data Science and advanced analytics.
This is a senior leadership position sitting at the intersection of
enterprise AI strategy, technical delivery and business transformation
.
The successful individual will help define how AI is developed, governed and deployed across the organisation, while leading multidisciplinary capabilities spanning Data Science, Data Engineering and AI Engineering.
The Role
As Head of Enterprise AI & Data Science, you will help define and govern the technical strategy for enterprise AI and advanced analytics.
Working closely with senior business, Digital and IT stakeholders, you will identify opportunities where AI can create measurable business value and oversee AI products throughout their lifecycle from feasibility and MVP development through to production deployment, scaling, monitoring and ongoing optimisation.
You will also lead the Data Science & AI Centre of Excellence, develop technical talent and drive the adoption of new AI technologies and methodologies across the organisation.
Key Responsibilities
Define and govern the technical strategy for enterprise AI, Data Science and advanced analytics.
Contribute to the broader enterprise AI strategy in partnership with business and technology leadership.
Lead AI and Data Science initiatives from feasibility and experimentation through MVP, production deployment, scaling and maintenance.
Establish enterprise standards, methodologies and best practices for AI development, deployment, governance and monitoring.
Ensure AI models are successfully integrated into existing systems and production environments.
Partner with business functions to identify and prioritise high-value applications for AI and advanced analytics.
Evaluate third-party AI technologies and solutions across technical performance, security, regulatory compliance and strategic fit.
Drive the adoption of enterprise AI and productivity solutions.
Establish metrics to measure the performance, adoption and business impact of AI initiatives.
Lead the Data Science & AI Centre of Excellence and foster the wider AI Engineering and Data Science community.
Lead, mentor and develop Data Scientists, Data Engineers and AI Engineers.
Communicate complex AI concepts and programme outcomes to senior business stakeholders.
Partner across Data, Digital, IT, Engineering, Legal, Privacy, Quality and Security.
Ensure appropriate AI governance and compliance with relevant regulatory requirements and standards, including emerging AI regulation.
Manage relationships with external AI vendors and technology partners.
Evaluate emerging AI technologies, methodologies and potential enterprise applications.
Experience Required
We are interested in speaking with senior AI leaders who combine
deep technical credibility with enterprise leadership and a business-centric approach
.
Ideally, you will have:
10+ years' experience within Artificial Intelligence, Data Science or a related field.
At least 5 years' experience in a leadership position.
Proven experience leading Data Science, AI Engineering and/or Data Engineering teams.
A track record of developing and implementing enterprise AI and advanced analytics solutions.
Experience taking AI products from concept and experimentation through to production and enterprise scale.
Strong expertise across
Machine Learning, Deep Learning, NLP, Generative AI, LLMs and Agentic AI
.
Experience with ML development and deployment frameworks including
PyTorch, Scikit-learn and MLflow
.
Strong knowledge of
Python, SQL and/or R
.
Experience within cloud Data & AI environments across
AWS and Azure
.
Exposure to technologies including
Databricks, Azure OpenAI, AWS Bedrock, S3, Glue and OpenSearch
.
Experience with Data Analysis, Transformation and Management technologies including
Pandas and DBT
.
Strong understanding of MLOps, AI productionisation and model monitoring.
Experience evaluating and implementing third-party AI technologies and platforms.
Understanding of AI governance, data privacy, security and regulatory requirements.
Experience working within a complex global matrix organisation.
Excellent senior stakeholder communication and influencing skills.
Experience within
pharmaceuticals or healthcare
would be particularly valuable.
An advanced degree (Master's or PhD) in Computer Science, Data Science, Artificial Intelligence or a related discipline is preferred.
This is an opportunity to take a highly visible enterprise leadership position within an organisation investing significantly in AI and Data Science, with the remit to influence how AI is developed, governed, deployed and scaled across the business.

## Artifact metadata

- Resume and cover letter: Not generated under the fit gate.
- Archived JD capture: https://files.keithsteward.com/LumaBio_Partners/Keith_Steward_head-of-enterprise-ai-and-data-science_4462153858_JD_capture.md
- Google Drive used: No