Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Product Analyst for NLP

Complexio
City of London
6 days ago
Create job alert
Overview

Complexio’s Foundational AI platform automates business processes by ingesting and understanding complete enterprise data—both structured and unstructured. Through proprietary models, knowledge graphs, and orchestration layers, Complexio maps human-computer interactions and autonomously executes complex workflows at scale.

Established as a joint venture between Hafnia and Símbolo—with partners including Marfin Management, C Transport Maritime, BW Epic Kosan, and Trans Sea Transport—Complexio is redefining enterprise productivity through context-aware, privacy-first automation.

We’re looking for a Product Analyst for NLP products who thrives in ambiguity, loves turning messy data into clarity, and can help drive product ideas forward with insight and speed. This isn’t a “traditional BA” role, nor is it a “corporate data science” one. You’ll be embedded with product and engineering teams and help us decide what to build this week, not six months from now.

What You’ll Do
  • Create specs (either in briefs or mock-up prototypes) that communicate to commercial stakeholders, product leadership, and data science—turning business needs and raw data into clear product opportunities
  • Specify products that don’t yet exist: innovative, data-driven offerings that are unique to us and may not have been seen in the market before
  • Work side by side with data scientists exploring our data to uncover hidden value—identifying signals, assembling datasets to bring new product ideas to life
  • Switch easily between strategic vision (‘what new product creates value?’) and technical realities (‘what data do we have or need?’)—proactively surfacing opportunities and driving them into prototypes or specs.
You’ll Be a Great Fit If You…
  • Comfortable with technology and data science concepts. You don’t need to be a software engineer, but you should be curious and hands-on—able to use agents/assistants to tinker, prototype, and bring ideas to life. ‘I’m not technical’ is not an option
  • You stay sharp on NLP and LLM advances — not just in theory but in how they can be applied creatively to products.
  • Self-driven motivation – you don’t wait for inspiration or step-by-step direction; you find energy in solving problems and building products, no matter the challenge
  • Love for the craft – genuine curiosity and enthusiasm for software, data, and product thinking. You enjoy the work itself, not just the outcomes
  • Startup awareness – experience to drop into an evolving situation, quickly understand the context, and identify how you can add value
  • Bias for contribution – instead of asking “what should I do?”, your instinct is to scan for gaps, propose solutions, and start creating impact
Benefits
  • Work with a groundbreaking AI platform solving real enterprise pain points
  • Help clients achieve measurable ROI through next-gen automation
  • Join a remote-first, globally distributed team backed by industry leaders
  • Shape the success function and influence product direction in a fast-scaling AI company
Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Analyst
  • Industries: Technology, Information and Internet


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Engineer – AI for Grid Innovation & Energy Transition

Senior Product Data Scientist

Senior Product Data Scientist

Senior Machine Learning Engineer

Principal Product Data Scientist

Principal Product Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.