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Data Engineer

Ground Truth Labs

GTL is a startup (Oxford University spinout) developing deep learning algorithms for image analysis to revolutionise precision medicine. GTL received a sizable seed stage investment from leading early stage investors in 2023. We grew from scratch to a team of 15 people, delivering commercial projects to some of the largest pharma and biotech companies in the world in less than a year. We are looking to continue our trajectory and develop novel algorithms and technologies to help positively impact patient lives. 

We deliver on the basis of our exceptional, interdisciplinary team. As an early team member, you'll have the unique opportunity to help shape our journey and build on our principles of collaboration, focus, and invention.

This is the new era of AI - we are on a mission to improve our understanding of biology and drive better patient outcomes through enhanced tissue analysis.

Your impact

We are looking for a Data Engineer to play a critical role in the development of new AI biomarkers for oncology.

This is a highly creative, fast-paced environment. Our teams are interdisciplinary, you will work alongside software, machine learning, and clinical science teams to build a rich interactive platform for the development and delivery of new AI tools.

We are an early stage company, you will have the opportunity to drive the strategic direction, lead on new projects and make an impact across the organisation. The successful candidate will be able to identify, build, and champion novel internal and externally facing tools across the company.

What you’ll do

  • Lead on data engineering from ingesting, through validation to persistence and maintenance

  • Define data requirements and validation procedures

  • Process data from various sources into a combined, curated database

  • Interrogate data for sensitive information

  • Build out automated pipelines to reduce and compliment human-in-the-loop requirements. 

  • Collaborate closely with machine learning scientists, software engineers and clinicians to deliver on new projects

  • Stay abreast of industry trends and standards  in healthcare data

What you bring

Essential

  • Proficient with Python, SQL, CSV, Excel

  • Experience working with Cloud Platforms, databases and APIs

  • Solid understanding of appropriate data formats and file types in data processing

  • Experience working both independently and as a part of a team environment

  • Experience using git or other version control software

  • Experience collecting requirements, writing proposals and managing projects

Nice to have

  • Degree in Computer Science, Engineering, or equivalent experience in science or engineering

  • Experience with GCP

  • Experience writing tests for data processing

  • Experience with healthcare or sensitive data

  • Experience working within a regulated environment 

  • Familiarity with modern machine learning and AI methods

Opportunity

Working environment

We primarily work remotely with a strong emphasis on efficient processes to ensure high-quality work across asynchronous teams. However, we recognise the importance of sharing knowledge and building relationships with one another and find this easier to do when we spend time together in-person in Oxford or London. Therefore, we host regular team days from these locations.

Exceptional candidates who are willing to regularly (~1/mo) travel to the UK for in-person meetings will be considered. This generally restricts us to candidates based within ~3 hour travel time to London. 

As a team, we value:

  1. Concise and engaging communication - we communicate clearly to work effectively in a remote setting.

  2. Pride in high-quality work - we pay attention to detail and deliver to the highest standard.

  3. A strategic approach - we think critically and creatively about complex issues. We identify the underlying patterns and leverage them to develop effective strategies

  4. Collaborative co-creation - we are open to diverse perspectives, bounce ideas off of each other, and build upon each other's strengths.

Equality

We welcome all applications. We are committed to providing equal employment opportunities regardless of age; disability; gender; civil status; pregnancy or parental status; race; religion or belief; sex; sexual orientation or any other basis as protected by applicable laws.

Impact

This is an excellent opportunity to join a rapidly growing start-up and make a real impact in the field of medical imaging and AI. If you are passionate about design, engineering, and AI and have a proven track record to match, we would love to hear from you.




No agencies please. 

Please note that when you submit an application, your data will be processed in line with our privacy policy.

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What You Should Know About Data Engineer, Ground Truth Labs

Join Ground Truth Labs (GTL) as a Data Engineer, and be part of a revolutionary startup emerging from Oxford University that’s on a mission to enhance precision medicine through innovative AI tools. Since our inception, we've rapidly grown into a dedicated team of 15, proudly delivering impactful commercial projects for leading pharma and biotech companies. As a Data Engineer at GTL, you’ll have the unique opportunity to drive strategic initiatives and collaborate with interdisciplinary teams comprising software engineers, machine learning scientists, and clinical experts. Your work will involve leading data engineering efforts including data ingestion, validation, and maintenance while building automated pipelines to maximize efficiency and minimize manual intervention. You will help construct a curated database by processing various data sources, ensuring compliance with the industry's standards for healthcare data. At GTL, we foster an inclusive, remote-focused work culture, balancing independent work with opportunities for collaborative in-person meetings in Oxford or London. Join us at this pivotal moment as we redefine how AI can transform biological understanding and ultimately improve patient outcomes. Your journey starts here, and with your expertise in Python, SQL, and data processing, together we can make a lasting impact in medical imaging and AI innovation.

Frequently Asked Questions (FAQs) for Data Engineer Role at Ground Truth Labs
What does a Data Engineer at Ground Truth Labs do?

As a Data Engineer at Ground Truth Labs, you will play a pivotal role in developing AI biomarkers for oncology. Your responsibilities include leading data engineering tasks, processing data from multiple sources, and building automated pipelines to streamline workflows. You’ll collaborate closely with interdisciplinary teams to help drive innovative projects in the field of precision medicine.

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What skills are required for the Data Engineer position at Ground Truth Labs?

To be successful as a Data Engineer at Ground Truth Labs, you should be proficient in Python, SQL, and data processing frameworks. Experience with cloud platforms, version control systems like git, and understanding various data formats is also essential. Familiarity with healthcare data and modern AI methods are advantageous but not mandatory.

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What is the work environment like for the Data Engineer role at Ground Truth Labs?

Ground Truth Labs promotes a primarily remote work environment, emphasizing efficient processes and communication among distributed teams. Regular in-person team days are hosted in Oxford or London to foster collaboration and relationship-building. Candidates should be prepared for occasional travel to the UK for these meetings.

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How can a Data Engineer impact healthcare at Ground Truth Labs?

A Data Engineer at Ground Truth Labs has a significant opportunity to influence the healthcare landscape by constructing robust data infrastructures that facilitate the development of AI-driven solutions for patient diagnosis and treatment. Your insights and data management capabilities can directly enhance the quality of healthcare delivery.

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What qualifications are ideal for a Data Engineer at Ground Truth Labs?

Ideal candidates for the Data Engineer position at Ground Truth Labs will possess a degree in Computer Science, Engineering, or related fields. Previous experience working with sensitive healthcare data and understanding regulatory environments will also be beneficial, preparing you for the unique challenges the role presents.

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Is Ground Truth Labs committed to diversity and inclusion in hiring?

Yes, Ground Truth Labs is dedicated to providing equal employment opportunities for all candidates regardless of their background. The company values diverse perspectives and fosters an inclusive environment for all team members, creating a culture where everyone can thrive.

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What can I expect during the interview process for a Data Engineer at Ground Truth Labs?

During the interview process for the Data Engineer role at Ground Truth Labs, you will likely engage in discussions about your technical skills, problem-solving abilities, and previous project experiences. Expect to answer questions that assess your data processing knowledge, your collaborative approach in interdisciplinary teams, and your views on innovative technologies in healthcare.

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Common Interview Questions for Data Engineer
What experience do you have with data processing pipelines?

When discussing your experience with data processing pipelines, provide specific examples of projects you've worked on. Describe the technologies you used and the outcomes of these projects, focusing on how you overcame challenges and improved data flow efficiency.

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How do you ensure the accuracy and quality of data?

To ensure data accuracy and quality, describe your methods for data validation and cleaning. Explain the processes you follow to check for inconsistencies and how you collaborate with other teams to maintain high standards of data integrity across the organization.

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Can you explain a time when you collaborated with a multidisciplinary team?

Share a specific instance that showcases how you worked alongside members from diverse fields, such as software engineering or clinical science. Emphasize the importance of communication, how you aligned project goals across disciplines, and what you learned from the collaboration.

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What cloud platforms are you familiar with, and how have you utilized them?

Discuss your experience with cloud platforms like GCP, AWS, or Azure, and explain how you have used these clouds in data storage, processing, and integration. Highlight any specific projects where cloud solutions were crucial in achieving project success.

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How do you approach data security, especially with sensitive information?

When answering, emphasize your understanding of data privacy regulations like HIPAA or GDPR and the best practices you implement to protect sensitive information. Describe the steps you take to secure data at rest and in transit.

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What programming languages are you proficient in, and why are they important for this role?

Talk about your proficiency in programming languages such as Python and SQL, which are crucial for data engineering tasks. Explain how proficiency in these languages allows you to process and analyze data effectively, streamlining the development of AI tools.

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Describe a challenging data-related problem you solved.

Provide a detailed narrative of a complex data challenge you encountered, the approaches you took to identify the issue, and the solutions you implemented. Focus on the impact your solutions had on project outcomes or team efficiency.

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How do you keep current with industry trends in data engineering?

Share your methods for staying updated, such as attending industry conferences, engaging with online forums, and following influential thought leaders in data engineering and healthcare AI. Highlight how you apply this knowledge to your work.

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What strategies do you use for effective communication in a remote setting?

Illustrate your communication strategies that promote clarity and collaboration, such as using project management tools or regular check-ins. Explain how you foster engagement and ensures everyone is aligned on project goals.

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How do you handle tight deadlines and high-pressure situations?

Discuss your strategies for time management and prioritization when facing tight deadlines. Share specific examples of how you maintained quality work under pressure and ensured timely delivery of project milestones.

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Full-time, remote
DATE POSTED
November 28, 2024

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