Global S&C_ATIOS_Strategy Consultant

Global S&C_ATIOS_Strategy Consultant

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Accenture UK

At a Glance

  • Tasks: Transform AI prototypes into enterprise-ready products and services.
  • Company: Join a dynamic team at QuantAI within Accenture, focused on innovative AI solutions.
  • Benefits: Competitive salary, hands-on experience, and opportunities for growth in a collaborative environment.
  • Other info: Small team with direct feedback and visible ownership of projects.
  • Why this job: Make a real impact by building trusted AI systems for major industries.
  • Qualifications: Bachelor's degree in relevant fields and strong coding skills in Python.

The predicted salary is between 60000 - 80000 £ per year.

Location: London

Career Level: 9 Consultant

QuantAI is building cutting‑edge AI‑native decision‑system assets for energy, commodities, financial, trading, and industrial operations. We are looking for engineers who can take strong quantitative and artificial intelligence (AI) work and turn it into enterprise‑safe products: interfaces, packaged desktop applications, APIs, services, workflow systems, and demos that are credible enough for pilots and durable enough for scaled delivery. Success here is not raw model novelty or polished demos in isolation. It is strong algorithms wrapped in workflow, governance, evaluation, and packaging. This role is engineer‑first and shipping‑first.

The engineering covers two surfaces that both ship as product: conventional systems on one side, agent‑assisted systems on the other. The team is too small for either to be someone else’s problem, and you should be able to operate across both -- though you will likely lead with strength in one.

What you’d work on:

  • Turn quantitative prototypes into reusable tools, services, packaged desktop applications, interfaces, and workflow products that can move from internal demo to client pilot to scaled offer.
  • Ship across both cloud‑hosted services and locally distributed desktop applications, including Electron‑based apps when the workflow or client environment calls for it.
  • Build enterprise hardening into the productization layer, including authentication, role‑based access control (RBAC), observability, security, release quality, cost controls, and deployment discipline.
  • Build evaluation, regression, and release discipline into the productization layer so model logic and agent behavior remain measurable as systems change.
  • Work closely with the quant lead so model logic, evaluation intent, and governance requirements survive the move into production.
  • Make pragmatic architecture choices across large language models (LLMs), deterministic rules, and hybrid systems based on value, latency, cost, and reliability.
  • Help shape repeatable build patterns so strong prototypes become faster, more reliable, and more reusable over time.

Platforms and interfaces:

  • Own data flows, APIs, services, model‑serving surfaces, front‑end and desktop application surfaces, continuous integration and continuous delivery (CI/CD), and demo hardening.
  • Build the systems that make quantitative work feel polished, reliable, and enterprise‑ready for expert users and client stakeholders.

Agent‑assisted systems:

  • Own the agentic harness layer — evaluation frameworks, reviewer loops, control‑plane behavior, orchestration, and tool integration — that applications and MCPs wrap around.
  • Design opinionated harnesses that expose through MCP or similar integration patterns without overfitting to one vendor or one moment in the tooling market.

What good looks like:

Must‑have:

  • Bachelor's degree in computer science, engineering, mathematics, physics, economics, or a related field. An associate degree is acceptable with at least 2 additional years of directly relevant experience and clear evidence of shipped engineering work.
  • Minimum 3 years of experience in consulting or other client‑facing technical delivery roles, with evidence that you have helped move products, internal tools, or workflow systems beyond proof‑of‑concept stage.
  • Minimum 3 years of hands‑on experience in one or more of the following areas: backend services, APIs and integrations, full‑stack delivery, data pipelines, model‑serving or machine learning workflows, or agentic orchestration systems.
  • Strong coding ability in Python plus one complementary engineering surface such as TypeScript or JavaScript, front‑end delivery, cloud or platform engineering, or infrastructure automation.
  • Sound engineering judgment around enterprise hardening and evaluation, including experience with several of the following: authentication, role‑based access control (RBAC), observability, security, release discipline, regression testing, or experiment frameworks for AI, machine learning, or agentic workflows.

Nice‑to‑have:

  • Experience with tool‑using systems, retrieval, evaluation pipelines, agent orchestration, or MCP‑style integrations.
  • Experience building expert‑facing interfaces, workflow products, or technical demos that had to stand up in front of real users.
  • Experience packaging desktop applications or supporting Windows‑heavy enterprise environments.
  • Exposure to forecasting, anomaly detection, optimization, time‑series systems, or other decision‑support workflows.
  • Experience in energy, commodities, financial, trading, market operations, or industrial workflows.

Team and environment:

QuantAI sits between quantitative research, agentic engineering, and product delivery inside Accenture. The team is small, hands‑on, and built for people who want visible ownership and the chance to build something lasting. The goal is not one‑off demos or deckware. The goal is reusable assets clients can trust, buy, and scale. Different strengths can thrive here, but on a team this size everyone works across both engineering surfaces. We care more about demonstrated depth in one area plus real fluency in the other than about a shallow checklist match across everything. You should expect direct technical feedback, growing scope, and close collaboration with quants and practice leadership. This is a small‑team build environment with real route‑to‑market access in energy, commodities, financial, trading, and industrial decision systems. The work needs to stand up in front of business decision makers and operators, not just engineers.

Equal Employment Opportunity Statement:

We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.

Global S&C_ATIOS_Strategy Consultant employer: Accenture UK

At QuantAI, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. Our small, hands-on team provides unique opportunities for personal and professional growth, allowing engineers to take ownership of their projects while developing cutting-edge AI solutions for real-world applications. With a commitment to diversity and inclusion, we create an environment where every voice is valued, ensuring that our employees can thrive and contribute to meaningful advancements in the energy and financial sectors.

Accenture UK

Contact Details:

Accenture UK Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Global S&C_ATIOS_Strategy Consultant

Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those that align with AI and engineering. Having tangible examples of your work can really set you apart during interviews.

Tip Number 3

Prepare for technical interviews by brushing up on your coding skills and understanding the latest trends in AI and engineering. Practice common interview questions and consider mock interviews to build confidence.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!

We think you need these skills to ace Global S&C_ATIOS_Strategy Consultant

Quantitative Analysis
Artificial Intelligence (AI)
Backend Services
APIs and Integrations
Full-Stack Delivery
Data Pipelines
Model-Serving Workflows

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the role of a Global S&C_ATIOS_Strategy Consultant. Highlight your coding abilities, experience in consulting, and any relevant projects you've worked on that showcase your engineering prowess.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your background makes you a perfect fit for our team. Be specific about your achievements and how they relate to the job description.

Showcase Your Projects:If you've worked on any relevant projects, especially those that moved beyond proof-of-concept, make sure to include them. We love seeing tangible evidence of your work, so link to any demos or applications you've built that demonstrate your skills.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our team!

How to prepare for a job interview at Accenture UK

Know Your Tech Inside Out

Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and any complementary languages like TypeScript or JavaScript. Brush up on your experience with APIs, backend services, and machine learning workflows, as these will likely come up during technical discussions.

Showcase Your Problem-Solving Skills

Prepare to discuss specific examples where you've taken a quantitative prototype and turned it into a reusable tool or service. Highlight your role in the process and the impact of your work, especially in client-facing scenarios. This will demonstrate your ability to deliver real value.

Understand the Business Context

Familiarise yourself with the energy, commodities, and financial sectors, as well as the challenges they face. Being able to speak knowledgeably about how your technical skills can solve industry-specific problems will set you apart from other candidates.

Be Ready for Collaboration Questions

Since the role involves working closely with quants and practice leadership, be prepared to discuss your experience in collaborative environments. Share examples of how you’ve successfully worked in small teams and how you handle direct feedback, as this is crucial for success in a hands-on team like QuantAI.