Tech Ops Data Scientist

Oxford Nanopore Technologies
Oxford
2 days ago
Create job alert

Job Description

Oxford Nanopore Technologies is headquartered at the Oxford Science Park outside Oxford, UK, with satellite offices and a commercial presence in many global locations across the US, APAC and Europe.

Oxford Nanopore employs from multiple subject areas including nanopore science, molecular biology and applications, informatics, engineering, electronics, manufacturing and commercialisation. The management team, led by CEO Dr Gordon Sanghera, has a track record of delivering disruptive technologies to the market.

Oxford Nanopore's sequencing platform is the only technology that offers real-time analysis, in fully scalable formats from pocket to population scale, that can analyse native DNA or RNA and sequence any length of fragment to achieve short to ultra-long read lengths. Our goal is to enable the analysis of any living thing, by anyone, anywhere!

We are looking for a highly motivated individual to join the Technical Operations team as a Data Analyst (Programmer), whose primary role is to extend our warehouse of data that underpins our work to support Manufacturing Operations, to include new sources of data.

The Details...

Part of the Technical Operations team's work is to monitor the performance of the flow cell manufacturing process in response to changes in the procedures, input materials or unforeseen events. This requires analysing data to identify associations between performance and its manufacture that inform decisions regarding what actions to take to improve performance. Much of this is achieved through the analysis of telemetry - data generated by testing and use of products - alongside data documenting how it has been manufactured. However, there are aspects of the manufacturing process that do not always represent processes sufficiently well to be able to reliably identify likely causes of performance issues.

This exciting and challenging role is responsible for extending the coverage of manufacturing data and analysing it to establish its explanatory power: to understand what aspects, if any, of manufacturing performance are associated with the data. To varying degrees, the role encompasses the entire data pipeline, including developing Extract-Transform-Load processes through to analysing data to establish associative and causal relationships.

Data that represents the quality of individual processes and input materials is a key component of the Predictive Manufacturing initiative which includes assessment and development of Causal Inference statistical techniques. Applicants with experience or interest in this area would have an opportunity to develop further in this discipline as it moves through proof-of-concept and applied stages of development.

The role will strengthen Technical Operations's analysis capability to:

  • provide more comprehensive coverage of data representing individual stages of flow cell manufacture
  • develop analysis procedures to assess, in the context of flow cell manufacture, the utility of existing and new data

Much of this will be achieved through development of tools in Python that can efficiently process, summarise and classify large volumes of data, creating pipelines that connect source databases to dashboards of results.

You will need to quickly establish a strong understanding of the science behind the product and convert data into insights of those factors associated with product performance and failure types.

What We're Looking For...

The ideal candidate will possess a numerate degree; for example in Mathematics, Statistics, Physics or Computer Science.

You will also be:

  • A strong python programmer
  • Have a good understanding of statistical concepts and principles
  • Proven ability to interpret data and understand underlying definitions
  • Possess good data instincts (assess degree of confidence in findings, detect data quality issues, identify inconsistencies, filter out chaff)
  • Possess excellent attention to detail, be inquisitive by nature
  • Able to apply scientific rigour and challenge assumptions
  • Have good presentation skills and confidently communicate and interact with multi-disciplinary teams.

Experience in some of the following routinely used technologies is expected:

  • Python (Pandas, numpy and Matplotlib/Seaborn)
  • MySQL
  • MongoDB
  • Spotfire/ Tableau
  • GitLab

Applicants should be highly motivated individuals who enjoy taking on new challenges, are quickly adaptable in an exciting and fast-paced environment, and who perform well under pressure.

We offer outstanding benefits to include an attractive bonus, generous pension contributions, private healthcare and an excellent starting salary.

If you are looking to utilise your skills to really make a difference to humankind, then consider joining our team and apply today!

Please note that no terminology in this advert is intended to discriminate on the grounds of a person's gender, marital status, race, religion, colour, age, disability or sexual orientation. Every candidate will be assessed only in accordance with their merits, qualifications and abilities to perform the duties of the job.

#LI-JC1

About Us

Oxford Nanopore's goal is to bring the widest benefits to society through enabling the analysis of anything, by anyone, anywhere. The company has developed a new generation of nanopore-based sensing technology enabling the real-time, high-performance, accessible and scalable analysis of DNA and RNA. The technology is used in more than 100 countries to understand the biology of humans and diseases, plants, animals, bacteria, viruses and whole environments.

Oxford Nanopore was founded in 2005 as a spin-out from the University of Oxford and now employs over 1000 employees around the world.#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Data Engineer - MLOps

Lead Data Engineer - MLOps

Data Scientist

Machine Learning and AI Engineering Lead

Senior Machine Learning Engineer

Senior Software Engineer, Machine Learning

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.

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

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

AI Jobs in the Public Sector: MOD, NHS & Gov Digital Service Opportunities

Artificial intelligence (AI) has rapidly evolved from a niche field of computer science into a transformative force reshaping industries across the globe. From healthcare to finance and from education to defence, AI-driven tools and techniques are revolutionising how we approach problems, improve efficiency, and make data-driven decisions. Nowhere is this transformation more apparent than in the United Kingdom’s public sector. Key government entities, including the Ministry of Defence (MOD), the National Health Service (NHS), and the Government Digital Service (GDS), are increasingly incorporating AI into their operations. Consequently, AI jobs within these bodies are growing both in number and strategic importance. In this comprehensive blog post, we will explore the landscape of AI jobs across the UK public sector, with a close look at the MOD, the NHS, and the Government Digital Service. We will delve into the reasons these organisations are investing heavily in AI, the types of roles available, the essential skills and qualifications required, as well as the salary ranges one might expect. Whether you are a new graduate keen to make a meaningful impact through your technical skills or a seasoned professional looking for your next career move, the public sector offers a wealth of opportunities in AI. By the end of this article, you will have a clearer understanding of why AI is so crucial to the public sector’s success, which roles are in demand, and how you can tailor your application to stand out in a competitive and rewarding job market.