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

Apply Now

Senior Data Scientist

JAC Recruitment (UK) Ltd.
City of London
1 week ago
Create job alert
Overview

AI startup company is looking for bilingual senior data scientist.


Working Pattern: Remote


Location: Worldwide


Language Requirement: Japanese and English fluency


As a company for whom AI is the product, it should be no surprise that our Data Science team is at the heart of everything - building innovative products, researching new techniques for using Artificial Intelligence in claims automation, and pushing the boundaries of what our product can achieve.


As a globally dispersed team, our Data Scientists bring together a diverse range of expertise and backgrounds; what unites us is a desire to learn, a mastery of our discipline, strong mathematical and statistical skills, and software engineering prowess. We typically specialise in fields such as Computer Vision, Natural Language Processing and Deep Learning.


Our Data Scientists are responsible for all aspects of the AI lifecycle, from understanding business problems, preparing training data, designing and building models, and deploying them into production. We work in cross-functional squads, so you will work collaboratively with other Data Scientists, Software Engineers, Product and Engagement Managers on projects specific to our Japanese customers.


You will not only lead the development of sophisticated ML models but also shape the future of our AI capabilities. You will have the opportunity to mentor junior team members, influence strategic decisions, and directly impact our customers’ experiences.


If you are passionate about transforming industries with AI and want to work with an innovative, ambitious team, we would love to hear from you. Apply now and help shape the future of claims automation.


Responsibilities

  • Develop features for our state-of-the-art claims automation platform
  • Research, build and deploy machine learning algorithms and models to production within product teams
  • Provide technical guidance and input on the design and implementation of machine learning algorithms
  • Support with customer PoVs and onboarding
  • Understand business problems and product requirements and help translate these into technical solutions
  • Execute and deliver full AI/ML solutions from sourcing training data, design and implementing state-of-the-art machine learning models, testing, benchmark and product-driven research for model performance improvement, to shipping stable, tested, performant code in an agile environment.
  • Work closely with Product Managers to help shape the product roadmap from a Data Science perspective
  • Contribute to Data Science strategy and the Data Science roadmap in conjunction with our Head of AI
  • Proactively seek to improve the way that Data Science operates
  • Support the education of the business and customers on how our Data Science teams work
  • Stay updated on the latest trends and advancements in Artificial Intelligence.

Skills, Knowledge, and Experience

  • Fluent Japanese and English speaking - this role will require you to work with complex Japanese documents and work with native Japanese speakers
  • Technical proficiency

    • You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance.
    • Comfortable with PyTorch
    • Knowledge of Transformer-based models
    • Knowledge of Large Language Models (LLMs)


  • Proven experience of having delivered successful either Computer Vision or LLM projects into production
  • Strong understanding of software development fundamentals, in particular deploying models to production and how to set up pipelines.
  • Can demonstrate a track record of delivering AI/ML solutions as an individual contributor
  • Demonstrate expertise in deep learning for computer vision, natural language processing, reinforcement learning etc
  • Displays in depth knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation
  • Strong fundamentals in Mathematics, Statistics and Data Analysis
  • Experience working in an Agile environment and knowledge of how Agile methodologies can be applied to Data Science teams in terms of process, practice, team culture and the delivery of work
  • Ability to convert customer requirements or business challenges into well-defined machine learning solutions

Compensation, benefits and perks

  • Share Options
  • 28 days’ annual leave (plus bank holidays)
  • Fully Remote role
  • Private Health Insurance + Dental Insurance
  • Learning and Development budget
  • Monthly socials, both in London and Virtual
  • WeWork perks - barista, social events, snacks etc.
  • Macbook Pro + home working setup


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist Customer Data

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior 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.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.