Data Scientist

Nexaphaze Ltd
London, England
8 months ago
Applications closed

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Are you a seasoned Data Scientist eager to collaborate with a team of top-tier innovators, tackling diverse products across various industries?

If so, Nexaphaze could be the perfect fit for you.

We’re seeking an experienced Data Scientist to join our team of innovators, working on cutting-edge projects for a diverse range of clients. You’ll collaborate with entrepreneurs and business leaders, helping them harness the power of data to drive business decisions, from early-stage MVPs to large-scale AI-powered products.

At Nexaphaze, you’ll be part of a cross-functional team with expertise in areas like fintech, AI, IoT, and more, solving complex problems and delivering meaningful insights.

What You’ll Be Doing:

As a Data Scientist, your responsibilities will include:

  • Collecting, analyzing, and interpreting large datasets to solve business challenges.
  • Building predictive models and machine learning algorithms to inform product and business decisions.
  • Collaborating with developers, engineers, and product teams to integrate data-driven solutions.
  • Conducting exploratory data analysis and creating dashboards to visualize insights.
  • Developing automated tools to process and analyze data at scale.

The Hands-On Experience You’ll Need:

  • 2+ years of experience working in data science or a related field.
  • Proficiency in programming languages like Python, R, or SQL for data manipulation.
  • Experience building machine learning models using libraries like TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with cloud platforms like AWS, GCP, or Azure.
  • Strong written and spoken English skills.

Bonus Experience:

  • Experience with big data tools (e.g., Hadoop, Spark) and distributed computing.
  • Knowledge of NLP techniques and libraries.
  • Familiarity with Docker, Kubernetes, and deploying machine learning models in production.
  • Experience with visualization tools like Tableau, Power BI, or D3.js.
  • Understanding of A/B testing, statistical analysis, and experimental design.

What You Can Expect from Our Recruitment Process:

  • We’ll start by reviewing your CV.
  • A one-hour interview with our recruitment team to get to know you better.
  • A one-and-a-half-hour technical interview to assess your skills.
  • A final one-hour interview to ensure we’re a mutual fit.
  • If you’re the right candidate, we’ll share the next steps to joining the Nexaphaze team.

What You Can Expect from Working with Us:

  • Competitive salary aligned with your experience.
  • Health insurance for you and your family.
  • Eligibility to work in London is required.
  • Flexible working hours and a remote-first policy, though we encourage you to join us at our pet-friendly office in London.
  • Team events, including weekly yoga sessions, summer surf days, Christmas dinners, and more.

Career Growth with Nexaphaze:

  • A clear career plan with strong growth potential.
  • A training budget to help you achieve your professional goals.
  • The chance to work on global projects with industry-leading clients.
  • A team of top talent innovators and researchers at your side.

If this opportunity excites you as much as it excites us, apply now to become part of the Nexaphaze team!


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Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.