Job Description

Lead Data Scientist

$175,000- $200,000

Pittsburgh, PA (Onsite)

THE ORGANISATION

A discreet, high‑growth technology group is expanding its advanced analytics and AI leadership capabilities. The organisation operates in a deeply complex environment where modelling, optimisation, and intelligent decision systems play a central role. They are investing heavily in next‑generation platforms that blend predictive modelling, simulation, and large‑scale automation to influence critical strategic choices.

THE ROLE

This is a senior technical and leadership role responsible for architecting sophisticated simulation, optimisation, and decision‑intelligence systems. You will guide the vision, design, and delivery of large‑scale AI solutions, combining hands‑on expertise with strategic leadership.

Your remit spans the development of system‑level simulations, optimisation engines, and complex modelling frameworks that support high‑impact decision workflows. You will define long‑range technical direction, lead major AI initiatives end‑to‑end, and mentor a highly skilled team of Data Scientists and AI Engineers.

This is a position for someone who thrives in ambiguity, enjoys solving multi‑variable, system‑level challenges, and brings strong conceptual and practical knowledge of advanced modelling.

KEY RESPONSIBILITIES

• Lead the architecture, design, and deployment of advanced simulation and optimisation platforms
• Build multi‑modal modelling systems incorporating predictive analytics, stochastic simulation, and strategic optimisation workflows
• Define the long‑term technical roadmap for modelling and decision‑intelligence initiatives
• Oversee large‑scale AI projects from initial scoping through to production launch
• Act as the senior technical authority on simulation, optimisation, and model strategy
• Develop scalable frameworks that support complex capability modelling and scenario analysis
• Lead the development of platform components that integrate simulation, optimisation, predictive modelling, and decision logic
• Mentor senior technical team members, raising the standard across modelling, experimentation, and delivery
• Establish modelling best practices, evaluation standards, and robust experimentation workflows
• Partner with cross‑functional teams to convert abstract, open‑ended challenges into concrete technical solutions
• Bring emerging research and methodologies (simulation techniques, optimisation methods, advanced model reasoning, etc.) into production systems
• Communicate modelling strategy, risk, and value clearly to both technical and non‑technical stakeholders

WHAT YOU BRING

• 7+ years of applied Data Science or similar experience in complex modelling domains
• Deep experience with simulation methodologies (e.g. discrete‑event, agent‑based, Monte‑Carlo, or similar approaches)
• Strong understanding of stochastic optimisation, Bayesian optimisation, and advanced mathematical modelling techniques
• Ability to design, evaluate, and scale large‑scale modelling systems and optimisation pipelines
• Strong Python engineering foundations and experience delivering production‑ready AI/ML systems
• Experience leading full lifecycle AI/DS projects, from ideation to deployment
• Proven track record of working with large datasets, complex modelling environments, and multi‑component systems
• Ability to mentor senior‑level technical staff and influence high‑level decision‑making
• Comfortable operating in a high‑autonomy, high‑ownership environment

DESIRABLE EXPERIENCE

• Experience with causal modelling, decision science, or structural modelling frameworks
• Experience with complex system evaluation, simulation benchmarking, or modelling validation
• Background in scaling AI/ML or optimisation systems across cloud environments
• Experience converting experimental prototypes into robust, enterprise‑ready solutions
• Strong publication or research contributions in modelling, optimisation, or related fields

THE OFFER

• Competitive Base Salary
• Opportunity to architect foundational modelling and optimisation systems for a major technology programme
• Significant autonomy and technical ownership
• Ability to shape modelling strategy, culture, and long‑term system design
• Work within a deeply technical team solving highly complex, meaningful challenges

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