Data Scientist

NTT
London
1 week ago
Create job alert

JOB DESCRIPTION

What you'll be doing:

Partner with business stakeholders to identify and prioritise opportunities where data science can deliver measurable value. Collect, clean, and transform structured and unstructured data from multiple internal and external sources. Develop, test, and deploy predictive models and machine learning algorithms to address business challenges. Conduct exploratory data analysis (EDA) to uncover trends, patterns, anomalies, and key drivers. Communicate insights and recommendations through clear storytelling, visualisations, and dashboards. Collaborate with engineering teams to productionise models and ensure reliability, scalability, and ongoing performance. Evaluate model accuracy and effectiveness, implementing continuous optimisation and tuning. Stay up to date with emerging data science tools, methodologies, and industry best practices.

Perform sensitivity analysis to assess model robustness and variable impact

What experience you'll bring:

At least 5 years’ experience in client‑facing data science roles with demonstrable impact on business outcomes. Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline. Strong proficiency in Python or R, including libraries such as pandas, scikit‑learn, NumPy, TensorFlow, or PyTorch. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Hands‑on experience applying a range of supervised and unsupervised machine learning techniques (, Random Forest, regression models, clustering methods). Proficiency with SQL and data warehousing technologies. Ability to translate complex analytical findings into clear, practical business recommendations. Strong problem‑solving skills and natural curiosity for exploring and understanding data.

Preferred Skills and Qualifications

Experience working with cloud platforms such as Azure, AWS, or Google Cloud. Background in deploying machine learning models into production environments (MLOps experience is advantageous). Hands‑on experience with big‑data or distributed computing tools such as Spark or Databricks. Familiarity with visualisation tools such as Power BI, Tableau, or Plotly. Industry experience in sectors such as retail, finance, healthcare, or similar (customisable).

Key Competencies

Strong analytical and conceptual thinking. Excellent communication and data‑storytelling capabilities. Effective collaboration and stakeholder‑engagement skills. High attention to detail and commitment to data accuracy.

Who we are:

We’re a business with a global reach that empowers local teams, and we undertake hugely exciting work that is genuinely changing the world. Our advanced portfolio of consulting, applications, business process, cloud, and infrastructure services will allow you to achieve great things by working with brilliant colleagues, and clients, on exciting projects.

Our inclusive work environment prioritises mutual respect, accountability, and continuous learning for all our people. This approach fosters collaboration, well-being, growth, and agility, leading to a more diverse, innovative, and competitive organisation. We are also proud to share that we have a range of Inclusion Networks such as: the Women’s Business Network, Cultural and Ethnicity Network, LGBTQ+ & Allies Network, Neurodiversity Network and the Parent Network.

what we'll offer you:

We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options.

You can find more information about NTT DATA UK & Ireland here: 

We are an equal opportunities employer. We believe in the fair treatment of all our employees and commit to promoting equity and diversity in our employment practices. We are also a proud Disability Confident Committed Employer - we are committed to creating a diverse and inclusive workforce. We actively collaborate with individuals who have disabilities and long-term health conditions which have an effect on their ability to do normal daily activities, ensuring that barriers are eliminated when it comes to employment opportunities. In line with our commitment, we guarantee an interview to applicants who declare to us, during the application process, that they have a disability and meet the minimum requirements for the role. If you require any reasonable adjustments during the recruitment process, please let us know. Join us in building a truly diverse and empowered team.

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist Placement

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.