Senior Optimisation Scientist UK
Role type: Full Time Contract
Location: UK timezone +/- 2 hours, Remote
Preferred Start Date: ASAP
Life as a Satalian (who we are)
As an organisation, we push the boundaries of data science, optimisation, and AI to solve the most complex problems in industry. Satalia (a WPP company) is a community of individuals devoted to working on diverse and challenging projects—allowing you to flex your technical skills whilst working with a tight-knit team of high performing colleagues.
Led by our founder and WPP Chief AI Officer Daniel Hulme, our ambition is to become a decentralised organisation of the future. This involves developing tools and processes to liberate and automate manual repetitive tasks, with a focus on freedom, transparency and trust. At the core of our thinking is an approach to wellbeing and inclusivity: we unpack human behaviour and unpick prejudice to ensure a safe and inviting environment. We offer truly flexible working and allow our employees to find the working practice that makes them most productive.
The Role (what we’re looking for)
As a Senior Optimisation Scientist, you will be part of a team who, together, design, develop, and productionise optimisation algorithms and decision-support tools across multiple industries (e.g. transportation, logistics, workforce scheduling, and media planning), operating end-to-end from problem discovery and mathematical modelling through to production deployment, robustness hardening, and measurable value capture.
You will collaborate directly with clients and internal stakeholders to translate operational challenges into tractable optimisation formulations and scalable software components, while also supporting peers through technical leadership, and code reviews in a flat, agile, interdisciplinary environment. In practice, you will act as a senior technical lead within a cross-functional product/delivery squad—partnering with software engineers, product, and domain experts—to deliver operationally critical decision-support capabilities end-to-end, including, but not limited to algorithms, data, integration, and runtime and observability).
Responsibilities (what you will be doing)
1) Algorithm Development & Modelling
Design and implement optimisation algorithms, including mathematical programming, decomposition approaches, and metaheuristics.
Structure problems end-to-end: define decision variables, constraints, objectives, feasibility/optimality trade-offs, and operational acceptance criteria.
Model both static and dynamic real-time optimisation and sequential decision-making problems.
Prototype and validate approaches quickly, then evolve these into robust, maintainable production components.
Select the right approach for the right job: explain trade-offs across exact methods vs. heuristics, runtime vs. optimality gap, and solution robustness vs. complexity.
2) Full-stack Production Readiness
Deliver production-ready code, implementing optimisation pipelines and services using best-practice software engineering (e.g., modular design, strict typing where applicable, automated testing, documentation).
Build and maintain robust data ingestion/cleaning pipelines supporting optimisation runs.
Integrate optimisation services into workflow orchestration layers and the wider product stack (APIs, UI hooks, scheduling/execution).
Implement reliability features: logging, monitoring/metrics, error handling, retries, fallbacks, and automated regression tests for operational edge cases.
Contribute to cloud-based deployment practices and CI/CD pipelines; ensure reproducibility, traceability, and safe releases.
3) Client Interaction & Value Realisation
Engage with clients to gather specifications, deeply understand the domain, and define what “value” means (service levels, cost, throughput, resilience, sustainability, etc.).
Communicate modelling choices and results clearly to audiences with varying technical depth; articulate assumptions, limitations, and validation evidence.
Quantify adoption and value capture: measure impact post-deployment and iterate based on operational feedback.
4) Technical Expertise & Team Contribution
Follow current and contribute to setting future engineering standards for optimisation components.
Provide code reviews; raise the bar on correctness, performance, readability, testability, and maintainability.
Mentor and train other team members on optimisation topics and delivery best practices.
Minimum Qualifications / Skills (what you need)
Relevant PhD or Master’s degree plus experience on applied optimisation problems, including experience in industry.
Deep expertise in at least one:
Mixed Integer linear programming, or
Metaheuristics, or
Stochastic programming, or
Reinforcement learning
Strong ability to structure and implement optimisation solutions in real-world settings.
Experience working in agile teams and cross-functional delivery environments.
Demonstrate technical leadership and/or team leadership.
Excellent written and verbal communication in English.
Reliability, accountability, collaborative mindset, and ability to give constructive feedback while supporting team wellbeing.
Deep programming expertise in at least one: Python, Java and/or Rust.
Familiarity with modern delivery tooling such as: cloud platforms, Git workflows, CI/CD, containerisation (Docker/ECS-style), experiment tracking/model/data versioning, and workflow orchestration patterns.
Behaviours and Mindset
Systems Thinker: detail-oriented while holding the big picture.
Curious, proactive, pragmatic, and data-driven.
Collaborative, resilient, and adaptable to changing priorities.
A technologist who keeps up with advances in optimisation, software development, and AI/ML.
Committed to delivering real operational value—not just mathematically elegant or over engineered models.
What we Offer
Benefits - enhanced pension, life assurance, income protection, private healthcare;
Remote working - café, bedroom, beach - wherever works;
Truly flexible working hours - school pick up, volunteering, gym;
Generous Leave - 27 days holiday plus bank holidays and enhanced family leave;
Annual bonus - when Satalia does well, we all do well;
Impactful projects - focus on bringing meaningful social and environmental change;
People oriented culture - wellbeing is a priority, as is being a nice person;
Transparent and open culture - you will be heard;
Development - focus on bringing the best out of each other;
If you feel like you don’t tick all our boxes but know you’d make a fantastic Senior Optimisation Scientist at Satalia, please do apply—transferable skills and experiences matter.
Satalia is home to some of the brightest minds in AI and if you’re looking to join a company who not only values autonomy and freedom, but embraces a culture of inclusion and warmth, we’d love to hear from you.
We aim to respond to all applications within 2 weeks. If you have not heard from us within 2 weeks this means your application has been unsuccessful. By applying to Satalia you are expressly giving your consent for the collection and use of your information as described within our Satalia Recruitment Privacy Policy. Good luck!
Relevant PhD or master's degree plus applied optimization experience in industry; expertise in a listed optimization method, deep Python, Java, or Rust skills, agile delivery, and technical leadership.
Key Responsibilities
- developing algorithms
- building pipelines
- mentoring teammates
Skills & Tools
Python, Java, Rust, Docker, Git, CI/CD, ECS, APIs
Job Details
- Category: Research and Development (R&D)
- Seniority: Senior Level
- Commitment: Full Time, Contract
- Workplace: Remote — United Kingdom
- Languages: English
Benefits
- Generous paid time off
- Retirement plan
- Generous parental leave
About Satalia
An artificial intelligence company developing optimization and decision-support solutions for complex industrial problems. — Industry: Information Technology