Chief Data Scientist

The Chief Data Scientist at Eliza will own the strategy, delivery, quality, and growth of all data science and machine learning work across client engagements. Unlike internal-only teams, your data team members work directly on customer projects, so you'll need to balance technical leadership, consulting discipline, sales/domain alignment, and execution excellence.
You will:Lead and scale the data science / AI practice as a core consulting pillarCollaborate deeply with sales, solution architecture, and delivery teamsEnsure high-quality, sustainable, scalable AI solutions delivered to clientsDrive innovation, methodology, and domain specializationRepresent Eliza externally (thought leadership, client-facing, industry presence)
Key Responsibilities
Strategic Leadership & Practice BuildingDefine the overall vision, strategy, and roadmap for Eliza's data science / AI practice (aligned with Fusion, Forge, and client engagement tracks).Identify key verticals, use-case domains, and technical specialization areas to develop deep expertise (e.g. agents, copilots, retrieval-augmented generation, prompt engineering, operational analytics).Partner with sales and pre-sales teams to help qualify data/AI opportunities, shape solution proposals, and ensure technical credibility.Drive hiring, training, and career development for data scientists, ML engineers, and analytics consultants — building a bench of billable talent.Establish metrics and KPIs for utilization, project margin, quality, and client satisfaction for the data practice.
Delivery Oversight & Quality AssuranceOversee delivery of data and AI work on client projects (from discovery, prototyping, to production).Ensure models and AI systems are robust, maintainable, interpretable, secure, and aligned with governance/compliance.Define best practices for model validation, monitoring, retraining, ML Ops, error handling, and observability.Set standards for code, architecture, documentation, data pipelines, and modular AI systems.Act as "escalation point" for technical risks, ensure client deliverables meet Eliza's quality bar and commitments.
Technical Leadership & InnovationKeep abreast of advances in LLMs, generative AI, multi-agent systems, embeddings, NLP, and aligned domains.Drive internal R&D / capability development (e.g. shared libraries, prompt tuning frameworks, agent templates, domain adapters).Foster knowledge-sharing, internal tooling, and cross-pollination across engagement pods.Evaluate and select AI/ML frameworks, platforms, infrastructure, and tooling to support scale and repeatability.
Client-Facing & Thought LeadershipServe as a senior advisor for strategic clients on data / AI adoption, architecture, roadmap, and risk mitigation.Present at conferences, publish whitepapers or blog posts, contribute to Eliza brand in the AI consulting space.Mentor client teams, build trust with executives, and drive adoption beyond proofs-of-concept.Governance, Ethics & RiskEnsure data privacy, security, and fairness practices are built into solutions.Establish guidelines for responsible AI, bias mitigation, documentation, and audits.Collaborate with legal, compliance, and security teams to ensure solutions meet enterprise-grade standards.
Qualifications & Experience
Must-Have:10+ years in data science / machine learning / AI, with consulting or client-facing experiencePrior leadership or senior management in a services / consulting environmentProven track record of delivering data/AI systems (from prototype to production)Deep technical expertise in Python, data engineering, ML frameworks (e.g. PyTorch, TensorFlow), LLMs, embeddings, NLP, MLOps, etc.Experience scaling and managing a team of billable data scientists / ML engineersStrong communication skills, able to bridge between executives, product, engineering, and clientsBusiness acumen and ability to shape proposals, manage budgets, and ensure margin discipline
Preferred / Differentiators:Master's or PhD in Machine Learning, AI, Computer Science, Statistics, or related fieldExperience specifically with generative AI, agent frameworks, prompt engineering, retrieval augmentationDomain experience in enterprise workflows, automation, productivity, or process optimizationConsulting mindset: ability to scope client work, manage change, work under ambiguityExperience contributing thought leadership (public talks, publications)
Success Metrics & KPIsUtilization & Billable Hours: high percentage of data team time allocated to client workProject Margin & Budget Adherence: ensure work is delivered profitable and within scopeClient Satisfaction / NPS: high feedback scores from clients on quality, outcomes, trustDelivery Quality / Defect Rates: few production failures, strong monitoring, low reworkInnovation Output: internal tools, reusable components, AI accelerators shippedPractice Growth: headcount, revenue from data/AI engagements, repeat business
Why This Role Matters at ElizaYou get to define and scale Eliza's AI-enabled data practice in a consultancy that is already deeply embedded in the OpenAI ecosystem.Your team will be directly contributing to high-impact client transformations, not just internal models.You'll influence how AI is embedded in real enterprises, from workflows to copilots to intelligent agents.You'll help shape the future of Eliza as a brand in AI consulting, building both capability and reputation.

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