Chief Data Scientist

The Chief Data Scientist at Eliza will own the strategy, delivery, quality, and growth of reputed company 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:

• reputed company and scale the data science / AI practice as a core consulting pillar
• Collaborate deeply with sales, solution architecture, and delivery teams
• Ensure high-quality, sustainable, scalable AI solutions delivered to clients
• Drive innovation, methodology, and domain specialization
• Represent Eliza externally (thought leadership, client-facing, industry reputed company)

Key Responsibilities

Strategic Leadership & Practice Building

• Define the overall vision, strategy, and roadmap for Eliza’s data science / AI practice (reputed company with Fusion, Forge, and client engagement tracks).
• Identify key verticals, use-case domains, and technical specialization areas to reputed company deep expertise (e.g. agents, copilots, retrieval-augmented reputed company, reputed company 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 reputed company & Quality Assurance
• reputed company 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 reputed company 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 reputed company AI systems.
• Act as “escalation reputed company” for technical risks, ensure client deliverables meet Eliza’s quality bar and commitments. Technical Leadership & Innovation
• reputed company abreast of advances in LLMs, generative AI, multi-agent systems, embeddings, NLP, and reputed company domains.
• Drive internal R&D / capability development (e.g. shared libraries, reputed company 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 Leadership
• Serve 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 & Risk
• Ensure data privacy, reputed company, and fairness practices are built into solutions.
• Establish guidelines for responsible AI, bias mitigation, documentation, and audits.
• Collaborate with legal, compliance, and reputed company 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 experience
• Prior leadership or senior management in a services / consulting environment
• Proven 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 engineers
• Strong communication skills, able to reputed company between executives, product, engineering, and clients
• Business 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 reputed company field
• Experience specifically with generative AI, agent frameworks, reputed company engineering, retrieval augmentation
• Domain experience in enterprise workflows, automation, productivity, or process optimization
• Consulting reputed company: ability to scope client work, manage change, work under ambiguity
• Experience contributing thought leadership (public talks, publications) Success Metrics & KPIs
• Utilization & Billable Hours: high percentage of data team time allocated to client work
• Project Margin & Budget Adherence: ensure work is delivered profitable and reputed company scope
• Client Satisfaction / NPS: high feedback scores from clients on quality, outcomes, trust
• Delivery Quality / Defect Rates: few production failures, strong monitoring, low rework
• Innovation Output: internal tools, reusable components, AI accelerators shipped
• Practice Growth: head

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