Lead AI & Data Scientist
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Job Description
Lead AI & Data Scientist at Trustwell, defining and implementing AI strategies across products and engineering. Collaborating with teams to enhance AI capabilities and governance.
Responsibilities:
- Define and help execute Trustwell’s applied AI strategy across product, engineering, data, and internal business operations.
- Lead the implementation of AI capabilities that are practical, measurable, secure, and aligned to business outcomes.
- Establish AI governance practices, including usage policies, risk controls, evaluation standards, approval processes, and ongoing monitoring.
- Partner with Engineering to design repeatable AI implementation patterns for LLMs, agents, retrieval-augmented generation, structured outputs, model evaluation, observability, and production operations.
- Partner with Product to identify, evaluate, and prioritize AI-enabled product opportunities that improve customer value and operational efficiency.
- Develop frameworks for assessing AI use cases, including feasibility, risk, data availability, implementation complexity, cost, and expected business impact.
- Create and maintain standards for responsible AI usage, including data handling, prompt management, model selection, explainability, auditability, and human-in-the-loop controls.
- Build and guide AI evaluation processes, including test datasets, regression testing, hallucination detection, quality scoring, accuracy measurement, and production feedback loops.
- Help establish internal AI adoption processes, including development workflows, engineering enablement, training, approved tooling, and practical usage guidelines.
- Work with Security, Legal, Compliance, and IT stakeholders to ensure AI implementations align with Trustwell’s data protection, privacy, contractual, and security obligations.
- Analyze structured and unstructured data to identify opportunities for automation, prediction, classification, summarization, enrichment, and decision support.
- Develop prototypes, proofs of concept, and production-ready analytical or AI workflows where appropriate.
- Provide technical leadership on model selection, vendor evaluation, build-versus-buy decisions, AI cost management, and long-term platform strategy.
- Collaborate with data engineering and application teams to improve data readiness, data quality, metadata, lineage, and retrieval strategies for AI-enabled systems.
- Define metrics and reporting to measure AI adoption, performance, quality, cost, risk, and business impact.
- Act as a trusted advisor and mentor to engineering, product, and business teams as they adopt AI responsibly and effectively.
- Other duties as required.
Requirements:
- 8+ years of professional experience across data science, machine learning, AI engineering, data engineering, software engineering, or related technical disciplines, with demonstrated experience leading applied AI initiatives from concept through implementation.
- Direct experience establishing or operating AI governance, evaluation, adoption, or production-readiness processes within an organization.
- Hands-on experience implementing AI or machine learning capabilities in a production, enterprise, or customer-facing environment.
- Strong understanding of modern AI technologies, including LLMs, embeddings, retrieval-augmented generation, prompt engineering, structured outputs, agentic workflows, and model evaluation.
- Experience translating business problems into practical AI, data science, analytics, or automation solutions.
- Ability to evaluate AI use cases based on business value, technical feasibility, data readiness, operational risk, and implementation cost.
- Experience establishing responsible AI practices, including data privacy, security, bias awareness, explainability, human review, auditability, and acceptable use controls.
- Strong analytical skills with the ability to work with structured and unstructured data.
- Experience with Python and common data science, machine learning, or AI development libraries and frameworks.
- Familiarity with APIs, cloud services, data pipelines, vector stores, and production software delivery practices.
Benefits:
- Full healthcare benefits, including medical, dental, and vision.
- Supplemental benefits, including STD, LTD, HSA, 401k, etc.
- Responsible Time Off (PTO) + Holiday Pay
- Competitive Compensation + Bonus!
- Excellent culture, growth opportunities, plus much more...
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