Data Scientist

BSI
Cambridge
1 year ago
Create job alert

Data Scientist (Innovation)


Cambridge, United Kingdom – Hybrid 2 days/week in office
About the role

As a Data Scientist within the Innovation team, you will work as part of a small, experienced team to drive maximum value from a deep and diverse range of data, using innovative technologies and techniques. You will partner with internal and external stakeholders, colleagues and professionals to collect and leverage data, and help craft innovative solutions to problems, while helping BSI continue to build trust and step into deeply digital ways of working.


Responsibilities

  • Use data science techniques to progress the digital evolution of BSI product offering (Generative‑AI etc.).
  • Mine and analyse BSI wide data to drive optimisation and improvement of product development, marketing techniques and business strategies.
  • Conduct end‑to‑end analysis that includes scoping, data gathering, ongoing deliverables and presentation.
  • Develop and present demonstrations and pilots to communicate the opportunities present by data science analysis in BSI.
  • Engage with data owners across the organisation to identify data science opportunities to ethically leverage BSI business data and drive solutions.
  • Maintain a portfolio of tools and technologies to ensure that BSI is prepared to leverage a diverse range of both structured and unstructured data and continually assess their efficiency and accuracy.
  • Use predictive modelling to increase and optimise business outcomes and services to clients.
  • Stay up to date with latest technology, requirements and methods and conduct research to develop prototypes and proof of concepts.
  • Look for opportunities to use insights, datasets, code and models across other functions in BSI.

To be successful in the role, you will have

  • Strong statistical analysis skills.
  • Extensive knowledge of Python (preferred) or R.
  • Knowledge of predictive modelling techniques.
  • Strong script/coding skills.
  • SQL Database experience.
  • Previous experience with Cloud Software (Azure/AWS).
  • Understanding of risk, ethics and compliance in relation to AI and technology.
  • Strong verbal and written skills.
  • Ability to translate and communicate technical language to non‑technical stakeholders.

It is not required, but would be advantageous for you to have

  • Previous experience in reviewing others' code.
  • Experience with Databricks.
  • Hands‑on AI technology experience.
  • Azure Dev Ops experience (managing data science tasks etc.).

Benefits

Grow your career and expand your skills and knowledge. At BSI, we offer opportunities to work across industries and across the globe. You’ll benefit from the different perspectives and experiences of your international colleagues, as well as ongoing training and development. We offer flexible working, as well as 27 days’ annual leave, paid sick leave, bank holidays, health insurance, life insurance, pension plan with company contribution, car allowance (dependent on role), income protection, paid maternity leave, paid paternity leave, paid parental leave, adoption leave, compassionate leave, paid bereavement leave, learning and development opportunities, and a wide range of flexible benefits that you can tailor to suit your lifestyle.


D&I Policy

The world needs fresh thinking and new perspectives to tackle its biggest challenges. It’s why, at BSI, we’re committed to creating a collaborative environment where everyone can contribute. Whatever your background, experience or outlook, here you can be your best self and do your best work.


If you have a disability or a health condition, please let us know if you need any reasonable adjustments to the recruitment process.


About Us

BSI is a business improvement and standards company and for over a century BSI has been recognised for having a positive impact on organisations and society, building trust and enhancing lives.


BSI is an Equal Opportunity Employer dedicated to fostering a diverse and inclusive workplace.


#LI-NC1


#LI-HYBRID


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist - Supply Chain Optimisation

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.

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.

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.

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

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.