Principal Data Scientist

Lorien
London
5 days ago
Create job alert

Lorien are currently working with a leading organisation that services academic & global institutes, R&D, health and medical sector.


We are supporting them in the recruitment of a Principal Data Scientist that will play a key role in driving the development of fast-paced experimental projects and Proof of Concepts (PoCs).


You will collaborate with multiple internal teams and external stakeholders to refine business strategies through innovative data science solutions. This role is integral to the success of cross-functional teams focused on shaping the future of technology solutions.


Responsibilities:


  • Work closely with internal teams across the organization to assess current data science and technology capabilities. Partner with business units to understand their strategic objectives and identify opportunities for innovation.
  • Lead the hands-on development of PoCs and experimental initiatives using a variety of technologies and advanced data science techniques. Form agile, cross-functional teams to rapidly validate concepts with end-users and refine strategies.
  • Serve as a subject matter expert in the field of Data Science and Advanced Technologies, including AI, Machine Learning, and GenAI. Keep the team updated on the latest industry trends and advancements. Present findings to senior leadership and at company-wide events.
  • Cultivate relationships with key stakeholders within client organizations, particularly in regulated industries. Identify challenges and opportunities within their technology ecosystems and provide expert insights on trends and solutions.
  • Assist in transitioning successful PoCs and experimental projects into production-ready solutions. Encourage and support cross-functional teams to accelerate time-to-market for impactful innovations.
  • Contribute to the creation and evolution of strategic technology roadmaps. Help guide the technology vision for the business and support the execution of key initiatives.


Experience:


  • A solid engineering background, with deep expertise in AI/ML technologies.
  • Practical experience in developing and supporting production systems as either a software developer or data scientist.
  • Proven leadership experience in managing teams to deliver complex, high-impact solutions, particularly across international and distributed teams.
  • Demonstrated success in implementing and integrating advanced data science technologies, including AI/ML and GenAI, into production environments.
  • Strong cross-functional communication skills, including stakeholder management and the ability to present technical insights at the executive level
  • Proficiency in Python and experience with additional languages and technologies such as Java, LangGraph, knowledge graphs, vector search, and no/low-code frameworks.
  • Familiarity with cloud platforms and tools such as AWS Sagemaker, Databricks, Snowflake, or similar.


The role is based on a hybrid basis at their Central London office.

Related Jobs

View all jobs

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist

▷ [Immediate Start] Principal Data Scientist

Head of Data Science and AI

Get the latest insights and jobs direct. Sign up for our newsletter.

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 Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.