Job at a Glance
- 📍 Location: Dubai, United Arab Emirates
- 🏢 Company: Kingston Stanley
- 💼 Employment Type: Full-time
- 📊 Seniority: Mid-Senior level
- 🗂️ Function: Analyst, Design, and Information Technology
- 🏭 Industry: Public Relations and Communications Services
- 📅 Date Posted: 2026-08-12
- 🌐 Category: Artificial Intelligence
About the Role & Company
Kingston Stanley has an open Artificial Intelligence Specialist role based in Dubai, United Arab Emirates. This position joins a Artificial Intelligence function that continues to attract investment in the UAE market. The upside for a the right person is straightforward: growing teams promote from within more often than mature ones. Day-to-day you’d be working across the scope typical of a Artificial Intelligence Specialist — a mix of delivery and stakeholder work. The UAE market for artificial intelligence talent hasn’t cooled — compensation is competitive and net pay stays high thanks to the tax setup. It’s a solid entry point for candidates who want regional exposure without giving up ownership of real work — you’re contributing, not observing.
Key Requirements
- Bachelor’s degree in Data Science, Computer Science, Analytics, Statistics, or a related field (or equivalent experience)
- Experience with Power BI, Tableau, Looker Studio, Excel, or similar BI tools
- on experience with generative AI, large language models, prompt engineering, or NLP
- Demonstrated understanding of PR, media intelligence, social listening, reputation, or digital communications measurement
- Ability to translate complex data into clear, actionable business insights
- Hands-on time with experience in PR analytics, media intelligence, communications strategy, or digital marketing analytics
- Experience building dashboards, reporting automation, and internal AI tools
- Knowledge of AI governance, bias evaluation, and explainable AI
Job Description
Data & AI Specialist to join one of our clients, supporting PR, communications, and business growth through AI-powered analytics, measurement, and automation. This role sits at the intersection of data science, artificial intelligence, media intelligence, and strategic communications , helping teams turn complex data into actionable insights while driving the accountable adoption of AI across the business.
Integrate AI into agency workflows and communications processes.
Design AI-driven solutions for media analysis, sentiment, audience insights, search visibility, and content performance.
Build dashboards, automated workflows, prompts, and lightweight AI tools.
Use AI and analytics to support PR measurement, reputation tracking, trend analysis, and strategic decision-making.
Partner with strategy, digital, creative, and analytics teams to build data-driven solutions.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this Artificial Intelligence Specialist opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, Machine Learning, NLP, Statistics, SQL, TensorFlow, PyTorch, Deep Learning, LLM, Computer Vision. ATS parsers match exact strings, not synonyms.
- Use a single-column layout. Two-column resumes break parsers — text gets scrambled or dropped.
- Save as .docx or standard .pdf (not scanned/image PDF). Avoid text boxes, headers, footers, graphics.
- Use standard section headings: Experience, Education, Skills, Certifications.
- Mirror the exact job title (Artificial Intelligence Specialist) in your target role line where truthful.
- Quantify results with numbers, percentages, currency. Metrics improve ATS scoring and human review.
- Spell acronyms out once (e.g., Search Engine Optimization (SEO)) so parser catches both forms.
- Font: Arial, Calibri, or Times New Roman at 10-12pt. Fancy fonts can render as unreadable glyphs.
Top 10 Interview Questions for This Role
- Walk me through your background and why you’re interested in this role.
- Describe a challenging project you owned end-to-end. What was the outcome?
- Tell me about a time you disagreed with a stakeholder. How did you handle it?
- How do you prioritize when everything on your plate feels urgent?
- How do you decide between fine-tuning a model vs. prompt engineering?
- Explain overfitting to a non-technical stakeholder.
- Walk through your data validation pipeline for training data.
- How do you evaluate model performance beyond accuracy?
- Describe your MLOps setup — from experimentation to production.
- How do you handle model drift once a system is in production?
How to Apply
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