- Company Name
- TekRek
- Job Title
- Director, Data Science and Artificial intelligence (AI)
- Job Description
-
**Job title**
Director, Data Science and Artificial Intelligence (AI)
**Role Summary**
Lead enterprise‑wide data science and AI strategy, scaling delivery from concept to production. Own roadmap, set governance standards, and guide multidisciplinary teams to deliver measurable business outcomes in a regulated financial services environment.
**Expectations**
- 10+ years in data science, analytics, or applied AI with clear business impact.
- 5+ years of leadership in scaling analytics/AI teams within complex organizations.
- Proven track record of moving research into production‑grade solutions with full ownership of adoption and performance.
- Deep technical expertise in Python/R, modern ML frameworks, Databricks, and cloud platforms (Azure/AWS).
- Strong foundation in experimentation design, model evaluation, monitoring, and AI governance.
- Executive‑level communication skills and experience in regulated or high‑trust settings.
**Key Responsibilities**
- Own and update the enterprise roadmap for advanced analytics, machine learning, and Gen AI initiatives, steering use cases from discovery to production.
- Establish and enforce standards for hypothesis design, controlled experiments, model evaluation, impact tracking, and continuous improvement.
- Lead, mentor, and grow multidisciplinary teams across discovery, prioritization, adoption, and lifecycle management.
- Partner with engineering and architecture to deliver reusable, production‑ready patterns on Databricks in Azure and AWS environments.
- Integrate governance into all delivery stages, covering privacy, security, compliance, documentation, monitoring, drift management, and audit readiness.
**Required Skills**
- Leadership and scaling of data science/analytics teams.
- End‑to‑end delivery from research to production, with ownership of performance and adoption.
- Programming: Python and/or R; ML frameworks (e.g., TensorFlow, PyTorch, scikit‑learn) and Databricks.
- Cloud expertise: Azure Data Services, AWS Machine Learning stack, and big‑data platforms.
- Experimentation, hypothesis testing, model evaluation, monitoring, and drift detection.
- AI governance, privacy, security, and compliance in regulated environments.
- Executive communication and stakeholder management.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, or related field (PhD preferred).
- Cloud certifications (e.g., Microsoft Azure Data Scientist, AWS Certified Machine Learning – Specialty) preferred.