Data Scientist

Nexaphaze Ltd
London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

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!


#J-18808-Ljbffr

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.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. 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.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.