Decision Analytics Manager​/Senior Manager

EY Parthenon is looking for a Decision Analytics Manager to join our high-performing Decision Modeling amp Economics practice focused on high-impact work in the Government and Public sector This is a hands-on technical role focused on data science and operational research leading advanced analytics engagements that improve strategic operational and investment decisions The role primarily supports government and public sector clients across the GCC with selected work across infrastructure energy investment education and transactions The successful candidate will bring deep expertise in data science or operational research supported by strong consulting and leadership skills and the breadth to lead multidisciplinary teams review technical work and translate analysis into practical recommendations The role is open to qualified candidates across MENA with flexibility on the final hiring location for the right candidate

You are likely to spend your day-to-day leading analytics work streams that help government and public sector entities make better decisions from problem definition and data assessment through modeling validation and implementation Assignments may include workforce and capacity planning network and supply-chain optimization economic and market forecasting transaction analytics capital-allocation modeling and strategic scenario analysis You will translate ambiguous business and policy questions into clear hypotheses methods and measurable outcomes and develop predictive forecasting optimization or simulation models suited to the decision and the available data You will also apply analytics to transaction and corporate-finance questions including customer performance concentration recurring revenue investment cases value creation and capital allocation You will provide technical leadership by selecting proportionate methods technology and development approaches for each engagement and by directing data scientists engineers analysts economists and modelers including code and model reviews You will set standards for testing documentation version control reproducibility and model governance identify data-quality methodological bias privacy and implementation risks and define mitigations and guide the transition from prototype to repeatable tool production solution or client-owned process Where appropriate you will identify and implement AI-enabled and agentic workflows across proposal development analytical quality assurance research and reporting with human review and approved data-governance controls You Will lead day-to-day relationships with client counterparts and senior stakeholders facilitating workshops to define decisions constraints success measures and analytical requirements You Will test scenarios and sensitivities explain methods assumptions and limitations clearly to non-technical audiences and translate findings into executive-ready insights recommendations presentations decision tools and dashboards that allow stakeholders to explore options and outcomes You Will define adoption measures performance indicators and benefits-tracking approaches so that analytical solutions are used effectively and deliver measurable decision value while managing team responsibilities technical reviews risks budgets and timelines In addition you will coach junior colleagues through technical guidance feedback and on-the-job learning helping to create a positive learning culture within the team You Will contribute to proposals solution design scoping effort estimates and client presentations identify follow-on opportunities and articulate the client value of analytical solutions You will also develop reusable methods code model templates and analytical accelerators and help convert successful project solutions into repeatable offerings and recurring analytical services such as model refreshes forecasting cycles performance monitoring and reporting updates

Individuals who combine technical depth with structured problem-solving and confident client leadership will thrive in this environment Success in this role requires a strong grounding in data science statistics machine learning operational research or applied mathematics and the ability to turn ambiguous questions into clear analytical problems and practical decisions Furthermore you should exercise sound judgment in model selection validation interpretation and governance remain hands-on in…