- Company Name
- MISC. Recruiting
- Job Title
- Director of AI & Data Science
- Job Description
-
**Job Title**
Director of AI & Data Science
**Role Summary**
Lead the organization’s AI and data science strategy, building and scaling production‑grade ML/AI solutions across enterprise systems. Drive cross‑functional collaboration, governance, and ethical AI practices while mentoring a high‑performing technical team.
**Expectations**
- Deliver measurable business impact through AI/ML initiatives.
- Establish and maintain AI governance, compliance, and responsible AI frameworks.
- Secure Top‑Secret clearance eligibility.
**Key Responsibilities**
1. **Strategy & Leadership** – Develop and execute the company’s data science & AI roadmap; align initiatives with executive objectives.
2. **Team Management** – Build, mentor, and grow a multidisciplinary team (data scientists, ML engineers, AI researchers).
3. **AI Governance** – Define ethical AI policies, bias mitigation, model explainability, and regulatory compliance (GDPR, CCPA, HIPAA).
4. **Technical Delivery** – Oversee end‑to‑end lifecycle: model design, data engineering, deployment on cloud platforms (AWS SageMaker, Azure ML, GCP Vertex, Databricks).
5. **Innovation & Partnerships** – Engage with academia, industry, and government partners to adopt cutting‑edge AI services (OpenAI, Gemini, Agentic AI) and pipelines.
6. **Project Management** – Translate strategy into prioritized roadmaps, manage resources, track KPIs, and ensure timely delivery.
7. **Cross‑Functional Collaboration** – Work with product, engineering, marketing, finance to embed data‑driven decision making.
8. **Communication** – Articulate complex AI concepts to non‑technical stakeholders.
**Required Skills**
- Advanced mastery of statistical modeling, deep learning, and ML frameworks (TensorFlow, PyTorch, Caffe, MS Cognitive Toolkit).
- Proven expertise in deploying AI models at scale on AWS, Azure, GCP, and Databricks.
- Proficiency in Python, R, SQL, and big‑data technologies (Hadoop, Spark, EMR).
- Strong knowledge of AI risk management, bias mitigation, model explainability, and responsible AI principles.
- Excellent strategic thinking, problem‑solving, communication, and presentation skills.
**Required Education & Certifications**
- Master’s or Ph.D. in Data Science, Computer Science, Statistics, or related field.
- Minimum 10 years in data science/AI, with 5 years in senior leadership.
- Eligibility to obtain Top‑Secret clearance.
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