Senior Decision Scientist

Visionary Tech Services LLC; Abu Dhabi; On-site; AED 200,000 - 250,000; Full time

Job summary

A leading technology consulting firm is seeking a Senior Decision Scientist to design complex decision systems and lead the development of end-to-end solutions. The ideal candidate will have over 6 years of experience in optimisation and simulation, and proficiency in Python and SQL. Responsibilities include mentoring associates, running technical workshops, and translating insights into actionable decisions. This role promises to offer substantial influence in policy and automation processes.

Qualifications

• 6+ years practical experience with optimisation and simulation.
• Ownership of end-to-end decision solutions in production or pilots.
• Experience mentoring others and establishing modelling standards.

Responsibilities

• Lead the translation of ambiguous goals into robust models.
• Select modelling approaches and design modular architectures.
• Run technical workshops and drive adoption of insights.

Skills

Python

SQL

Optimisation (LP/MILP)

Simulation (DES/ABM)

Causal inference

Education

Bachelor’s or Master’s in a relevant quantitative field

PhD preferred

Job description

As a Senior Decision Scientist at VTS, you will own the design and delivery of complex decision systems. You’ll lead the translation of ambiguous goals into robust models and decision products, combining optimisation, simulation, causal evidence and GenAI to inform policy and automation and realise value for our clients.

Requirements

• Bachelor’s or Master’s in Operations Research, Econometrics, Industrial Engineering, Applied Mathematics, Data Science, or a related quantitative field. PhD preferred.
• 6+ years practical experience with optimisation (LP / MILP, heuristics) and simulation (DES / ABM), plus working knowledge of causal inference or experimentation at scale
• Demonstrated ownership of end‑to‑end decision solutions in production or pilots
• Proficient in Python and SQL with strong engineering practices; comfortable with containers and CI / CD; experience integrating models into services, workflows, or apps
• Able to choose and justify methods, diagnose performance, and communicate trade‑offs to technical and non‑technical stakeholders
• Experience mentoring others and establishing modelling standards and review practices
• Problem framing : Lead discovery to define decision objectives, constraints, KPIs, and data readiness; quantify expected value and risks
• Architecture and methods : Select modelling approaches, design modular architectures, and combine optimisation, simulation, and causal evidence when appropriate
• Build and scale : Implement core models, performance‑tune solvers / simulators, and integrate with data pipelines, APIs, and front‑end experiences
• Experimentation and evaluation : Design robust experiments or quasi‑experiments; set evaluation protocols, stress tests, and rollback plans
• Reuse and standards : Create reusable components, templates, and documentation; uplift code quality, testing, and observability
• Stakeholder leadership : Run technical workshops, translate insights into decisions, and drive adoption with clear narratives and visuals
• Mentorship : Review associate work, coach on method selection and design, and help set sprint scope and acceptance criteria