- Company Name
- South Pole
- Job Title
- Director of Data & AI
- Job Description
-
**Job Title:** Director of Data & AI
**Role Summary:**
Senior executive responsible for designing, scaling, and governing enterprise-wide AI initiatives. Leads the Data & Insights team, bridges raw data silos, and drives AI adoption across business units, aligning technical strategy with business objectives and ethical standards.
**Expectations:**
- Deliver measurable ROI through AI projects.
- Maintain data governance, privacy, and compliance.
- Cultivate an AI‑first culture and capacity within the organization.
**Key Responsibilities:**
- **Strategic Vision & Alignment** – Map AI opportunities, formulate enterprise AI roadmap, advise senior leadership on trends, risks, and competitive advantage.
- **Governance & Ethics** – Establish responsible AI frameworks, data privacy, and transparency policies.
- **Portfolio Management** – Oversee pipeline from PoC to production, ensuring technical feasibility and business impact.
- **Data Readiness & Architecture** – Conduct AI‑readiness audits, design AI pipelines, select vector databases, MLOps tools, and data ingestion workflows.
- **Implementation Leadership** – Remove blockers, manage cross‑functional teams, monitor model performance, define KPI dashboards for deployed models.
- **Organizational Upskilling & Change Advocacy** – Partner with People & Culture to develop training programs, online learning channels, and adoption metrics; educate leadership on AI timelines and workforce impact.
- **Stakeholder Navigation** – Act as liaison among IT, Engineering, Legal, Marketing, Finance, and other functions to align objectives and deliver integrated solutions.
- **Team Leadership** – Coach the Data & Insights team from traditional BI to advanced analytics, enforce data quality, and promote collaboration across business lines.
**Required Skills:**
- Executive stakeholder management and cross‑functional leadership.
- Deep knowledge of AI/ML lifecycle (data prep, labeling, fine‑tuning, RAG, deployment).
- Experience with MLOps platforms, vector databases, model monitoring, and KPI definition.
- Data governance expertise: privacy, compliance, ethical AI.
- Ability to translate technical solutions into business value and ROI.
- Strong communication, change‑management, and training delivery skills.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field (Master’s or MBA preferred).
- Certifications in AI/ML, MLOps, or data governance (e.g., DataOps, TensorFlow, AWS ML or Azure AI) are advantageous.
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