Your Role

We’re looking for a Lead Data Scientist to join our Global Football Metrics data science team, which is focused on delivering innovative machine learning models to keep Hudl at the cutting edge of sports analytics.

As a Lead Data Scientist, your key responsibilities will include:

• Work with a cross-functional team. You’ll collaborate with Engineering, Quality Assurance, Product, Design and Scrum disciplines to deliver cutting-edge tactical and recruitment insights.
• Develop and deliver. You will have access to industry-leading data from a variety of sources, and will lead the research and development roadmap for new Global Football models and metrics.
• Test new ideas. At Hudl, we iterate rapidly, deploying changes to the product hundreds of times daily across our Engineering team. In addition to working on concrete metrics, you’ll contribute to the implementation of scalable data pipelines and associated orchestration and monitoring tools.
• Mentor. You’ll share your expertise and educate others on development best practices and trade-offs, setting an example in planning, designing and delivering complex projects, and maintaining high standards of statistical rigour.

We’d like to hire someone for this role who lives near our office in London, but we’re also open to remote candidates. Remote candidates would have the ability to work from a co-working space or their home.

Must-Haves

• Technical expertise. You have a strong background in a quantitative discipline, and proven experience implementing statistical and machine learning models for statistical inference in complex systems.
• A team player. You understand that problem-solving is a team effort and will help others on our Engineering team learn and develop their skills.
• User-focused. You’re excited to have your work used by real people to solve real problems.
• Willing to learn. You have solid engineering skills but are always willing to dive into specific areas to gain the expertise needed to be successful in your role.

Nice-to-Haves

• Sports industry experience. If you’ve worked with event or tracking data previously, that’s a plus.
• Tech stack knowledge. Our tech stack is Python, PostgreSQL and Redshift. We will consider strong candidates with experience of R or Stan, but prefer those with more full stack skills and capable of writing production code.

Our Role 

• Champion work-life harmony. We’ll give you the flexibility you need in your work life (e.g., flexible vacation time above any required statutory leave, company-wide holidays and timeout (meeting-free) days, remote work options and more) so you can enjoy your personal life too.
• Guarantee autonomy. We have an open, honest culture and we trust our people from day one. Your team will support you, but you’ll own your work and have the agency to try new ideas.
• Encourage career growth. We’re lifelong learners who encourage professional development. We’ll give you tons of resources and opportunities to keep growing.
• Provide an environment to help you succeed. We've invested in our offices, designing incredible spaces with our employees in mind. But whether you’re at the office or working remotely, we’ll provide you the tech you need to do your best work.
• Support your wellbeing. Depending on location, we offer medical and retirement benefits for employees—but no matter where you’re located, we have resources like our Employee Assistance Program and employee resource groups to support your mental health.

Compensation

As a Staff Data Scientist, you will lead innovation in experimentation and causal inference, helping shape the future of decision-making and product innovation at SIE. You will drive innovative research in experimentation methodologies while mentoring other team members. You’ll be responsible for elevating our experimentation strategy, fostering a culture of curiosity and rigor, and helping cross-functional teams deliver player-first experiences through strong evidence-based decisions.

What You’ll Be Doing:

• Drive innovation in experimentation research by shaping measurement frameworks and best practices, and by developing new methodologies that enhance the quality, speed, and scalability of experiments.
• Advance experimentation infrastructure and tooling, incorporating statistical and machine learning methods to refine analytical capabilities.
• Mentor and guide less-senior data scientists, building expertise in experimentation and causal inference while providing technical direction to ensure rigor and impact.
• Partner with product managers and business leaders to identify high-impact experimentation opportunities and align them with PlayStation’s strategic goals.
• Act as a thought leader in experimentation and causal inference, evangelizing best practices and fostering learning across teams.
• Contribute to research and prototyping of novel experimentation techniques that address complex real-world challenges, such as user behavior variability and data limitations.
• Champion a data-driven culture by establishing experimentation standards, ethical practices, and reproducibility
• Represent the team’s insights and innovations across the broader data science and product communities within PlayStation.
• Stay at the forefront of the field by monitoring emerging developments in experimentation, causal inference, and applied machine learning to continuously evolve capabilities.

What We’re Looking For:

• Master’s Degree or equivalent experience in Applied Math, Economics, Statistics, Computer Science, or related field. Ph.D. or equivalent experience preferred.
• Strong familiarity with the gaming industry and contemporary gaming experiences.
• 8+ years of experience in data science, including extensive hands-on work in experimentation, with at least 2+ years in a mentoring or technical leadership capacity.
• Proven track record of leading experimentation innovation and scaling frameworks within a dynamic business environment.
• Proficiency in SQL and statistical programming languages (e.g., R or Python), especially for causal inference, experimental analysis, and scalable modeling.
• Expertise in causal inference techniques and designing both randomized and quasi-experiments.
• Demonstrated ability to collaborate cross-functionally and influence data strategies that inform business and product decisions.
• Excellent communication and storytelling skills, especially in conveying complex concepts to non-technical stakeholders.
• Experience working with modern data engineering and visualization tools (e.g., Airflow, Git, Tableau, MicroStrategy).
• A strong sense of ownership and an inclusive leadership style that encourages collaboration and innovation.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks.

Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. 

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm.

Your future role within QRT

This team is integral to the firm’s success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and to inform discretionary trading decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
• Managing the end-to-end process of onboarding new datasets
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

Your present skillset

• 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering.
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Demonstratable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist with strong experience in index data. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of index data across the firm's systematic strategies.

Your future role within QRT

This team is integral to the firm's success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design and maintain index and ETF datasets that drive systematic strategies and inform discretionary trading decisions

• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats, including index constituent data, benchmark compositions, weightings, rebalancing schedules, ETF holdings and flows, and associated reference data

• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes

• Managing the end-to-end process of onboarding new index and ETF datasets, including equity indices, fixed income indices, ETFs, custom baskets, and related benchmark products

• Proactively solving data related problems to minimise time to production

• Innovating and experimenting with novel data extraction methods to enhance the firm's data onboarding toolkit

Your present skillset

• 2+ years of experience as a Data Scientist (or similar position) working with index or ETF data, benchmark data, or index-linked financial products; experience in a buy-side quantitative finance role is strongly preferred

• Solid understanding of index construction, constituent methodology, rebalancing mechanics, ETF structure and flows, and the role of benchmarks in systematic and portfolio-level strategies

• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering

• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy

• Proven experience building and managing data pipelines end-to-end; from sourcing and extraction through to cleaning, processing, and delivery

• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors

• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are looking for an exceptional Data Scientist with a strong fixed income background. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data across the firm's fixed income strategies and beyond.

Your future role within QRT

This team is integral to the firm's success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders, particularly within fixed income, to design datasets that drive systematic strategies and inform discretionary trading decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats, including fixed income market data, reference data, and pricing feeds
• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
• Managing the end-to-end process of onboarding new datasets, with a focus on fixed income instruments such as bonds, rates, credit, and derivatives
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm's data onboarding toolkit

Your present skillset

• 2+ years of experience as a Data Scientist (or similar position) working with fixed income data; experience in a buy-side quantitative finance role is strongly preferred
• Solid understanding of fixed income markets and instruments including bonds, interest rates, credit, yield curves, or related derivatives
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Proven experience building and managing data pipelines end-to-end; from sourcing and extraction through to cleaning, processing, and delivery
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

About the Synthetic Chemistry, CMC and Logistics team

Our dynamic team of Synthetic Chemists and CRO Leads are dedicated to transforming drug design and manufacturing. We work in partnership with our AI/ML and drug discovery colleagues to support all phases of chemistry, from early to late stages, as well as managing our extensive external CRO team. We promote a supportive atmosphere where the diverse expertise of every team member is recognised and appreciated. We maintain a strong growth mindset, with continuous development and learning as a priority.

If you are a skilled and ambitious scientist looking to take the next step in your career, joining Isomorphic Labs will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

Your impact

As part of the ongoing expansion of our Drug Design and Medical Research function, we are hiring Synthetic Chemists who are keen to impact medicinal chemistry projects and/or CMC projects. You will support the business alongside world-leading AI/ML Drug Design Platform teams. You will deliver scientific expertise and strategic direction to drive improvements in the Platform and the advancement of active drug discovery programs.

What you will do 

• Apply your Synthetic Chemistry expertise across Medicinal Chemistry and/or CMC projects.
• Act as a Synthetic Chemistry Lead in one or more active drug discovery programs.
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams to support the data-driven delivery of high quality scientific solutions to complex technical problems.
• Work cross-functionally with the Medicinal Chemistry, DMPK, Biology, and Technology teams.
• Represent the company externally, interacting with existing and prospective collaborators including Contract Research Organisations (CROs) and Contract Development & Manufacturing Organisations (CDMOs).
• Prepare detailed scientific proposals and reports to support new and ongoing programs.
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in Synthetic Chemistry, or a related technical field, or equivalent industrial experience.
• 3+ years’ professional experience in a Chemistry role, operating within a biotech, pharma or CRO setting. 5+ years' experience for more senior positions.
• Solid technical foundation in synthetic chemistry with previous experience operating independently as an individual contributor.
• Excellent problem-solving and decision-making capabilities applied to complex synthetic chemistry challenges.
• Experience of working with and closely managing CRO and/or CDMO resources.
• A genuine passion for drug discovery and enthusiasm for the potential of AI/ML to transform the field.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
• Track record of creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

About the DMPK and Quantitative Pharmacology team

The DMPK and Quantitative Pharmacology team, part of the Preclinical Development group, accelerates the delivery of high quality drug candidates by developing innovative and creative AI-first solutions. By applying our domain expertise and through collaboration with the entirety of our world-class drug discovery disciplines and ML researchers, we ensure that drug-like properties are at the heart of our drug design engine. We shape the development of state-of-the-art ADME and toxicology predictive models. We rethink drug discovery from Hit ID to first-in-human (FIH) trials by optimising the context of use of these models.

Your impact

At Isomorphic Labs, DMPK Leads drive the DMPK strategy of drug discovery and development projects to deliver high quality clinical candidates whilst using and contributing to the optimisation of state-of-the-art computational and AI ADME models. 

As part of the Drug Design and Medical Research team and through close collaboration with the Technology teams, you will support the business alongside world leading AI/ML Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to real drug design projects. You use your expertise in PBPK modelling to make data integration a powerful tool to accelerate drug design and preclinical development.

If you are a skilled and ambitious scientist looking to take the next step in your career, joining the Isomorphic Labs now will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

What you will do 

• Define Iso’s PBPK strategy leading to fit for purpose models that drive drug design and accelerate accelerate preclinical development.
• Design and implement stage-appropriate development DMPK strategies with AI-first approach, integrate the quantitative pharmacology and overall project strategies.
• Design mechanistic experiments to support project progression in a data-driven manner.
• Integrate DMPK, PD and toxicological data to extract decision-making information, including dose and safety window predictions.
• Define Quantitative Pharmacology strategy in collaboration with Pharmacology Leads.
• Optimise molecule design and formulation based on physico-chemistry and biotransformation knowledge in collaboration with Chemistry Leads.
• Maintain knowledge of state-of-the-art technologies and methods to increase confidence in human PK prediction.
• Author DMPK sections of regulatory documents.
• Embrace and champion a culture of inclusion and continuous professional development.
• Optimise the use of Iso’s datasets to address fundamental DMPK questions and advance the field.

Skills and qualifications 

Essential:

• PhD in either Pharmaceutical Science, Pharmacy, Chemistry, or another relevant subject.
• 5+ years’ professional as a DMPK Lead, solving DMPK-related problems in preclinical development with a track record of working collaboratively to deliver regulatory-ready FIH packages.
• Practical experience in setting up automated PBPK workflows.
• Practical experience in using PBPK to support preclinical development.
• Practical experience developing DMPK and quantitative pharmacology packages to support early clinical development, including authoring and reviewing regulatory documents, ideally in oncology.
• Advanced knowledge of PK and PKPD modelling.
• Experience of partnering closely with Preclinical and Clinical teams.

Nice to have:

• Experience with biologics, peptides and other new modalities.
• Good understanding of machine learning techniques.
• Familiarity with Python and KNIME.

About the DMPK and Quantitative Pharmacology team

The DMPK and Quantitative Pharmacology team, part of the Preclinical Development group, accelerates the delivery of high quality drug candidates by developing innovative and creative AI-first solutions. By applying our domain expertise and through collaboration with the entirety of our world-class drug discovery disciplines and ML researchers, we ensure that drug-like properties are at the heart of our drug design engine. We shape the development of state-of-the-art ADME and toxicology predictive models. We rethink drug discovery from Hit ID to first-in-human (FIH) trials by optimising the context of use of these models.

Your impact

At Isomorphic Labs, DMPK Leads drive the DMPK strategy of drug discovery projects to deliver high quality clinical candidates whilst using and contributing to the optimisation of state-of-the-art computational and AI ADME models. 

As part of the Drug Design and Medical Research team and through close collaboration with the Technology teams, you will be supporting the business alongside world leading AI/ML Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to real drug design projects. 

If you are a skilled and ambitious scientist looking to take the next step in your career, joining Isomorphic Labs will lift you out of your comfort zone and provide you with an amazing opportunity for personal growth and development.

What you will do 

• Design and implement stage-appropriate DMPK strategies with AI-first approach, integrating quantitative pharmacology and overall project strategies.
• Design screening cascade and mechanistic experiments to support project progression in a data-driven manner.
• Integrate DMPK, PD and toxicological data to extract decision-making information, including dose and safety window predictions.
• Define Quantitative Pharmacology strategy in collaboration with Pharmacology Leads.
• Optimise the use of Iso’s datasets to address fundamental DMPK questions and advance the field.
• Optimise molecule design based on physico-chemistry and biotransformation knowledge in collaboration with Chemistry Leads.
• Maintain knowledge of state-of-the-art technologies and methods to increase confidence in human PK prediction.
• Author DMPK sections of regulatory documents.
• Embrace and champion a culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in either Pharmaceutical Science, Pharmacy, Chemistry, or another relevant subject.
• 3+ years’ professional experience as a DMPK Lead, solving DMPK-related problems in drug discovery with a track record of working collaboratively to deliver high quality candidates.
• Practical experience developing DMPK and quantitative pharmacology packages to support early clinical development, including authoring and reviewing regulatory documents, ideally in oncology or immunology.
• Experience of partnering closely with Preclinical and Clinical teams.
• In depth knowledge of biotransformation.
• In depth knowledge of PK modelling and scaling of ADME properties.

Nice to have:

• Experience with biologics, peptides and other new modalities.
• Advanced knowledge of PKPD modelling.
• Good understanding of machine learning techniques.
• Familiarity with Python and KNIME.

About Graphcore

At Graphcore, we’re building the future of AI compute.We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale.As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem.To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world.We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Job Summary

As a researcher at Graphcore, you will contribute to the advancement of AI research, investigating new ideas that push the limits on important AI/ML problems. Specialised hardware has been the key driver of the progress of AI over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this exciting field. As such, we’re looking for candidates who are keen scientists and engineers, with the theoretical and practical skills needed for impactful AI research.

We are looking for researchers with experience of AI in low-power, edge and embodied scenarios such as robotics, autonomous driving and augmented/virtual reality. We are interested in the training and deployment of multimodal AI models in these contexts, covering areas such as world models, real-time computer vision, generating and reasoning over audio/video streams.

The Team

Graphcore Research participates in both fundamental and applied research, to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences (NeurIPS, ICML, ICLR) as well as specialist workshops, and collaborate with other research teams and organisations across the world.

We pride ourselves on being a supportive and collaborative team, where we organise around our individual research interests to solve problems together in domains such as efficient compute, model scaling and distributed training and inference of AI models for multiple modalities and applications, including for sequence- and graph-based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations.

Perhaps the best way to get an idea of what we’re all about is to read one of our papers or an article on our blog. If you’re excited to work at the cutting edge of AI supported by new hardware and want to develop your skills in this area, we’d love to hear from you!

Responsibilities and Duties

• Generate AI/ML ideas, design experiments, implement them & evaluate results.
• Prepare, submit & present your work to AI conferences and workshops.
• Collaborate with researchers, silicon and software engineers at Graphcore to help define, build and test Graphcore’s next generation of AI hardware.

About you:

Essential:

• Master’s, PhD or equivalent experience in a technical discipline (e.g., Maths, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering).
• Experience in embodied AI, world models or robotics.
• Python programming in a modern deep learning framework, e.g. PyTorch or JAX.
• Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling.
• Capable of designing, executing and reporting from ML experiments.
• Mathematics skills to support the above: calculus, probability theory and linear algebra.
• Experience submitting papers to international scientific conferences or workshops.

Desirable:

• Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton.
• Practical familiarity with hardware capabilities for deep learning – threads, caches, vector & matrix engines, data dependencies, bus widths and throttling.
• Practical familiarity with software stacks for deep learning – compilation, kernel fusion, XLA/ATen ops, streams, and asynchronous execution.
• Conference or workshop submissions in the fields of embodied AI, world models, or robotics.

Benefits

In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.

Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

About the Exploratory Sciences Team

Join our expanding Exploratory Sciences team, focused on tackling proteins which are critical for disease biology, but have been traditionally considered intractable. We are a small, multidisciplinary team within the Drug Design and Medical Research function at Isomorphic Labs. We work at the interface of machine learning, chemical biology and drug discovery to apply our platform to some of the toughest problems in drug discovery, and we collaborate closely with multiple teams across Isomorphic Labs. We have a strong growth mindset and prioritise continued development and learning as we hope to build the next generation of drug discovery scientists.

We are expanding and investing in our multidisciplinary Induced Proximity team within Exploratory Sciences, looking to recruit a number of talented scientists to drive projects towards the clinic. This role is for a Chemistry Lead, specialising in induced proximity. We're also willing to consider applications from those with PhD experience in molecular glue design and synthesis but no professional experience yet, as we plan to open junior positions within this team in the near future.

Your impact

As a member of the Induced Proximity team, you will deliver the development and application of a state-of-the-art induced proximity design platform. This will involve applying our platform in novel ways, and critically driving portfolio projects towards the clinic. You will need to design and execute on bold strategies to tackle problems that are currently considered impossible. Working alongside world leading AI/ML and Drug Design Platform teams. You will collaborate to deliver scientific expertise and strategic direction to drive both improvements in the Platform and apply this to unsolved drug design problems.

Ready to elevate your scientific career? Isomorphic Labs offers ambitious scientists a unique environment to tackle stimulating challenges, pushing your boundaries and accelerating your personal and professional growth. If you are a skilled and ambitious scientist looking to take the next step in your career, joining the Isomorphic Labs will challenge you with novel problems and provide an unparalleled opportunity for professional growth and development.

What you will do 

• Apply your knowledge of cutting-edge molecular glue design and synthesis to tackle long standing challenges in drug discovery.
• Utilise internal AI/ML models to solve challenging drug discovery problems.
• Collaborate both internally and with third party organisations, interacting within multidisciplinary teams to support data-driven delivery of high quality scientific solutions. This will require understanding the fundamentals of diverse disciplines including ML, Biology, Chemistry and DMPK, and communicating effectively with experts in those fields. 
• Represent the company externally, interacting with existing and prospective collaborators and contract research organisations (CROs).
• Prepare detailed scientific proposals and reports to support new and ongoing programs.
• Embrace and champion our culture of inclusion and continuous professional development.

Skills and qualifications 

Essential:

• PhD in Chemistry, or a related technical field, or equivalent experience.
• 3+ years’ professional experience in a Chemistry role, either operating within a biotech or pharma setting, or within a Post Doc position.
• Practical experience in the design and synthesis of chemical inducers of proximity/molecular glues, ideally with experience of applying these skills to active drug discovery projects.
• Broad knowledge of current chemical biology techniques.
• Experience of coding in Python, or a willingness to learn in-role.
• A genuine passion and enthusiasm for applying AI/ML to drug design and how this can transform the field.
• Excellent communication (written and verbal) and interpersonal skills, with an ability to work effectively in a cross-functional, collaborative team environment.
• A track record of creative problem solving with a strong growth mindset, adaptability, and eagerness to learn new concepts and techniques.

Nice to have:

• Experience working with or managing activities at contract research organisations (CROs).
• Experience of contributing to structure-based drug design (SBDD) problems.
• Experience of applying ML methods to Drug Discovery problems.
• Track record of authorship of relevant scientific manuscripts.

The deadline for applying to this role is Sunday 24th May 2026, end of day, anywhere on Earth.

Team Description    

The ability to effectively evaluate and monitor AI systems will grow in importance as models become more capable, autonomous, and integrated into society. If models can detect and game evaluations, obscure their reasoning, or behave differently under observation, the safety claims that governments and developers rely on become unreliable. Understanding and addressing these risks is essential to ensuring that oversight of advanced AI systems keeps pace with their capabilities. 

The Model Transparency team is a research team within AISI focused on ensuring that evaluations, assessments, and monitoring of frontier AI systems remain reliable as models become less transparent. We research how and why oversight is declining – through phenomena such as evaluation awareness, unfaithful chain-of-thought reasoning, and changes in model architectures – and develop methods (including white and black box methods) to detect, measure, and mitigate potential issues. We share our findings with frontier AI companies (including Anthropic, OpenAI, DeepMind), UK government officials, and allied governments, and publicly to inform their deployment, research, and policy decisions. We also work directly with safety teams at frontier labs, contributing to safety case reviews and helping improve their alignment evaluation methodology. 

Our recent work includes auditing games for sandbagging, reproducing natural emergent misalignment from reward hacking, and identifying open-weight language models that game propensity evaluations. 

Role description

We're looking for Research Scientists and Research Engineers for the Model Transparency team with expertise in technical AI safety – such as interpretability, capability or alignment evaluations, model transparency – or with broader experience with frontier LLM research and development. An ideal candidate would have a strong track record of high-quality research in technical AI safety or adjacent fields. 

• Research Scientists, drive the technical substance of our work – staying abreast of the literature, proposing and designing experiments, conducting rigorous analyses, and owning the evidence stack from experiment through to written output. They write, critique, and strengthen the team's reports and publications. 
• Research Engineers, build the systems and tooling that make our research possible and fast – scaling experimental workflows, automating processes, solving infrastructure challenges, and creating systems that accelerate the entire team's output.

We're interested in candidates along the spectrum between Research Engineers and Research Scientists. The application form will ask you to indicate which role you lean towards. 

The team is led by Joseph Bloom, advised by Geoffrey Irving. You'll work with talented, mission-driven technical staff across AISI, including alumni from Anthropic, OpenAI, DeepMind, and top universities. You may also collaborate with external research teams including those at frontier AI labs, METR, and FAR. 

We are open to hires across a range of experience levels.

This role requires three days a week in person, with flexibility for occasional periods of remote working. 

Representative Projects You Might Work On

• Developing a chain-of-thought monitorability benchmark and comparing monitorability properties across frontier AI systems, leveraging AISI’s unique access to reasoning traces from multiple labs. 

• Designing and running experiments on open-weight models to study alignment and oversight-relevant phenomena – such as reproducing emergent misalignment from reward hacking, or red-teaming techniques like inoculation prompting and character training. 

• Using white-box and interpretability methods – such as activation oracles, sparse auto-encoders or probes – to detect misalignment that isn’t visible through behavioural evaluation alone. 

• Building tooling and infrastructure for our research – including agent orchestration, large-scale RL pipelines, mechanistic interpretability methodologies, and auditing agents. 

The work could also involve: 

• Reviewing frontier lab risk assessments and safety cases, providing independent analysis of alignment claims before deployment decisions. 
• Conducting literature reviews and expert interviews to map the state of model transparency risks and inform AISI’s strategic priorities. 
• Translating technical findings into actionable insights for AISI evaluation teams, UK government officials, and international partners. 

What we’re looking for   

If you’re unsure whether you meet the criteria below, we’d encourage you to apply anyway – we’d rather you erred on the side of applying than not. 

Requirements for both roles:

• A get-things-done mindset – you take ownership, move fast, and care about shipping work that matters. 

• A combination of self-sufficiency and enthusiasm for teamwork – you’re equally happy defining your own agenda and contributing to shared goals. You’re excited about growing, giving and receiving feedback, and building something together. 

• An ability to build, supervise and orchestrate AI agents to complete tasks effectively, while verifying and maintaining quality of work. 

• A demonstrated track record of relevant, high-quality work – whether technical publications, blog posts, or other publicly visible contributions. 

Research Scientists – our requirements are: 

• Hands-on research experience with large language models (LLMs) – such as evaluating or fine-tuning models, developing and testing monitors, or auditing models with white-box or black-box techniques. 

• Ability and experience in writing research code for machine learning experiments, including experience with ML frameworks like PyTorch or evaluation frameworks like Inspect. 

• An ability to write high-quality, concise research proposals that are well-motivated, tractable, and coherent. 

• Good research taste – an ability to identify what’s important, choose productive directions, and avoid getting lost in dead ends. 

• An ability to read research critically, identify flawed arguments, and poke holes in safety claims. 

We don’t expect RS candidates to meet all of the following, but they are useful signal: 

• Experience designing and running alignment evaluations or working on model transparency research. 

• Experience with interpretability or white-box methods – such as mechanistic interpretability, sparse autoencoders, probing, or activation analysis. 

• Familiarity with alignment literature, current methods for post-training and aligning LLMs, and the current state of the field. 

• Prior mentorship or training within technical AI safety – such as through the MATS program or similar. 

Research Engineers – our requirements are: 

• Strong software engineering skills and experience building systems that support ML research – infrastructure, pipelines, tooling, or experimental platforms. 

• Ability and experience writing production-quality code in Python and familiarity with ML frameworks like PyTorch. 

• Experience working with LLMs at scale in some capacity – fine-tuning, deploying, evaluating, or building scaffolds around them. 

• An understanding of the needs of research scientists, experience working within and supporting a research team or building tools to support research. 

We don’t expect RE candidates to meet all of the following, but they are useful signal: 

• A track record of scaling AI automation – getting agents to do useful work, building orchestration systems, or accelerating research workflows with AI tooling. 

• Experience working with very large models (~100B+) at scale, including post-training (RL, RLHF, DPO), fine-tuning pipelines, or distributed interpretability work on models that don’t fit into memory. 

• Experience with mechanistic interpretability tooling or white-box analysis infrastructure at scale. 

• Strong open-source contributions, particularly related to LLMs or AI safety. 

• Proficient usage of LLM coding tools and agents. 

Selection process  

Candidates should expect to go through some or all of the following stages: 

1. CV / application review 
2. Screening call
3. Technical assessment
4. Research interview
5. Behavioural interview
6. Final interview with members of the senior leadership team

What You’ll Do:

The Monolith Data Science team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. As a forward deployed function, we partner closely with Fleet, Infrastructure, and AI Platform teams to embed data science directly into production environments—improving cluster reliability, increasing effective utilization (MFU), reducing MTTR, and protecting uptime and revenue.

About the role:

As a Forward Deployed Data Scientist, you will work at the intersection of data science and production systems, deploying advanced statistical models and machine learning methodologies directly within operational environments. You will collaborate closely with engineering and infrastructure teams to optimize GPU utilization, workload scheduling, and system efficiency in real time. You will design experiments, analyze large-scale system telemetry data, and build predictive and optimization solutions that are tightly integrated into production workflows. This role blends hands-on deployment with analytical rigor, turning complex infrastructure data into measurable improvements in performance and cost. You will translate research and modeling insights into scalable, production-ready systems.

Who You Are:

• MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related quantitative field
• 8+ years (or equivalent experience) applying statistical modeling or machine learning to large-scale datasets
• Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow)
• Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing)
• Experience working with distributed data systems (Spark, Ray, Dask, or similar)
• Proficiency in SQL and working with large-scale structured datasets
• Experience building, deploying, and maintaining predictive models in production environments
• Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning)
• Experience working with time-series data and performance telemetry
• Ability to translate analytical insights into production-ready systems and workflows
• Strong collaboration skills and ability to work cross-functionally in fast-paced environments

Preferred:

• PhD with published research in systems optimization, distributed computing, ML systems, or performance modeling
• Experience with GPU workloads, distributed training, or AI infrastructure
• Familiarity with Kubernetes, containerized workloads, or cloud-native systems
• Experience deploying reinforcement learning or adaptive scheduling systems in production
• Background in capacity planning, forecasting, or resource allocation modeling
• Contributions to open-source ML or systems projects

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams—even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love uncovering hidden failure patterns in massive, noisy infrastructure datasets
• You enjoy working directly with engineering teams to deploy solutions that have immediate real-world impact
• You’re curious about building autonomous, agentic systems that investigate and explain system behavior
• You’re an expert in reinforcement learning, predictive modeling, or large-scale data analysis

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

ABOUT WORLDQUANT BRAIN

worldquantbrain.com

BRAIN is a group within WorldQuant similar to a traditional B2C fintech setup. Our mission is to simplify quant finance and provide global remote-work opportunities to participants, while they learn quant finance, AI and ML concepts. WorldQuant Brain provides an advanced crowdsourcing platform for external participants to contribute signals, data and more to the firm.

THE ROLE:

WorldQuant is seeking Researchers to join the BRAIN team. BRAIN is WorldQuant’s crowdsourcing initiative that allows anyone in the world with the right skills to become a Quant.

Research

• Create and develop Alphas and other utilization algorithms on BRAIN
• Conduct research on academic quantitative finance literature
• Identify and design new research domains. Generate ideas to grow the domain

Platform development

• Analyze current functionalities available to researchers, identify any issues with the platform and provide solutions and recommendations to the BRAIN team
• Design and test new functionalities and datasets on the BRAIN platform.

Business Development and Consultant Engagement

• Work with BRAIN Strategy and Operations country heads and other Business Development partners to enhance & implement BRAIN business strategy for user and consultant acquisition
• Conduct training sessions for BRAIN users and consultants
• Prepare and update training curriculum of BRAIN

WHAT YOU’LL BRING:

• Familiarity and competence in using BRAIN. Applicants expected to have Consultant status on the BRAIN Platform - worldquantbrain.com
• Possess or expect a Bachelor’s degree or advanced degree in engineering, science, mathematics, finance or any other related field that is highly analytical and quantitative from a leading university
• Demonstrated programming experience in one of the following (Java/C++/C/Python/MySQL/SQL Server); knowledge of UNIX preferred
• Possess a research scientist mind-set; be a self-starter, a creative and persevering deep thinker who is motivated by unsolved challenges
• Have a strong interest in learning about worldwide financial markets
• Possess good communication and presentation skills in English

Position based in London. Visit https://www.worldquant.com/brain/ for more information about WorldQuant Brain.

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

• For US-based candidates (Cambridge or San Francisco), we expect the base salary for this role to fall between $176,000–$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact.
• For UK-based candidates, compensation will be determined separately and will be aligned with local market benchmarks and internal leveling.

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Set the build and research strategy for Lila’s safety approach to biological / physical risks.
• Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences.
• Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use-cases.
• Develop and curate high-quality training and test data for evals and safety systems.
• Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general-purpose frontier models as well as narrow scientific tools)
• Contributing to broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.
• Contribute to external communications on Lila’s safety efforts.

What You’ll Need to Succeed

• A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience.
• Demonstrated ability to set research directions for open problems in dual-use risks in the biological / physical sciences.
• Experience in scientific computing, across either biological or physical sciences.
• Familiarity with dual-use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical-related conventions and controls).
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.
• Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point-of-view on biological / physical risks
• Demonstrated ability to deal with cross-functional stakeholders (science, AI, product, policy) in a complex environment.

Bonus Points For

• Experience in developing or applying ML to biological or physical sciences
• Experience in building evaluations, or conducting red-teaming exercises, across scientific risks for frontier models / narrow scientific tools.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

Your Impact at LILA

We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to prepare for risks from scientific superintelligence. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, as well as developing technical collateral including risk- and capability-focused evaluations and safeguards.

What You'll Be Building

• Evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs
• Initial proof-of-concept safeguards, such as ML models to detect and block unsafe behavior from scientific AI models, as well as from physical lab outputs.
• Understanding of a range of model capabilities, across primarily scientific but also non-scientific domains (e.g. persuasion, deception) to inform Lila's broader safety strategy.
• Broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.

What You’ll Need to Succeed

• Bachelor's degree in a technical field (e.g., computer science, engineering, machine learning, mathematics, physics, statistics), or related experience.
• Strong programming skills in Python, and experience with ML frameworks (including, for instance, Inspect) for large-scale evaluation and scaffolded testing.
• Experience in building evaluations, or conducting red-teaming exercises, for CBRN / cyber risks (or for frontier model capabilities more generally, including both unsafe and benign capabilities)
• Experience in designing and/or implementing (directly or through consultation) AI safety frameworks for frontier AI companies.
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.

Bonus Points For

• Masters or PhD in a field relevant to safety evaluations of AI models in scientific domains, or a technical field.
• Publications in AI safety / evaluations / model behaviour in top ML / AI conferences (NeurIPS, ICML, ICLR, ACL) or model release system cards.
• Experience researching risks from novel science (e.g. biosecurity, computational biology, etc.) or working with narrow scientific tools (e.g. large scale foundation models for science).

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

Job Title: Locum Vascular Scientist  
Banding: 7/8 
Location: Central London 
Start: 21/01/2025 
Duration: 3months 
Rate: £50- £60 
Working hours: Full time

We are seeking an experienced and highly skilled Locum Vascular Scientist to join our team in Central London. This is an excellent opportunity for a professional to work in a dynamic and supportive environment, providing specialized vascular diagnostic services. The successful candidate will be responsible for performing a range of vascular assessments and ensuring the highest standards of patient care.

What will your responsibilities be:

As a Locum Vascular Scientist, you will be tasked with conducting a variety of vascular assessments, including duplex ultrasound scans of the carotid arteries, peripheral arteries, and veins. You will engage closely with patients to explain procedures, ensure their comfort, and meticulously record test results. You will collaborate with vascular surgeons and other healthcare professionals to interpret test results and contribute to patient care plans. You will also be expected to maintain and calibrate equipment, adhere to clinical protocols, and stay updated with the latest advancements in vascular diagnostics. You will participate in quality assurance activities, assist in the training and supervision of junior staff, and contribute to the development of departmental policies and procedures. You will be involved in patient education, providing information on vascular health and lifestyle modifications. You will also manage inventory and supplies for the vascular lab, ensure compliance with health and safety regulations, and participate in research and development projects to enhance vascular diagnostic techniques and patient outcomes.

Qualifications and Experiences:

• Degree in Vascular Science or related field
• HCPC registration
• Extensive experience in vascular diagnostics
• Proficiency in duplex ultrasound scans of the carotid arteries, peripheral arteries, and veins
• Strong communication and interpersonal skills
• Ability to work independently and as part of a team
• Attention to detail and accuracy in recording test results
• Familiarity with the latest vascular diagnostic equipment and techniques
• Experience in quality assurance and clinical audit processes
• Ability to train and supervise junior staff
• Knowledge of health and safety regulations in a clinical setting
• Commitment to continuous professional development and staying updated with advancements in the field

Why work with Pulse? 

From the moment you register with us, our focus is entirely on you. During our first conversation, you’ll quickly see that we understand your specialty inside and out. 

Our expert recruitment consultants are dedicated to finding you the best opportunities and supporting you every step of the way to secure the perfect placement. With our preferred or sole supplier status with many clients, you’ll have access to exclusive opportunities that you won’t find anywhere else. 

We always prioritize your best interests, engaging in meaningful conversations and truly listening to you. You are an individual, a professional—not just a resource. 

Reasonable Adjustments:

If you consider yourself to have a disability or require any reasonable adjustment during the recruitment process or within the workplace, please highlight this at the earliest opportunity by contacting our team. With this information, we will provide appropriate support to you throughout the process and into your work placement. 

We are unable to support or accept applications from candidates who are residents within the Red or Amber list of the Code of practice for the international recruitment of health and social care personnel in England, based on the World Health Organisation (WHO) Workforce Support and Safeguard List. 

Job Title: Locum Vascular Scientist  
Banding: 7 
Location: Salisbury 
Start: 17/09/2025 
Duration: 3 months 
Rate: £50 – £60 
Working hours: Full time

We are seeking an experienced and highly skilled Locum Vascular Scientist to join our team in Salisbury. This is an excellent opportunity for a professional to work in a dynamic and supportive environment, providing specialized vascular diagnostic services. The successful candidate will be responsible for performing a range of vascular assessments and ensuring the highest standards of patient care.

What will your responsibilities be:

As a Locum Vascular Scientist, you will be tasked with conducting a variety of vascular assessments, including duplex ultrasound scans of the carotid arteries, peripheral arteries, and veins. You will engage closely with patients to explain procedures, ensure their comfort, and meticulously record test results. You will collaborate with vascular surgeons and other healthcare professionals to interpret test results and contribute to patient care plans. You will also be expected to maintain and calibrate equipment, adhere to clinical protocols, and stay updated with the latest advancements in vascular diagnostics. You will participate in quality assurance activities, assist in the training and supervision of junior staff, and contribute to the development of departmental policies and procedures. You will be involved in patient education, providing information on vascular health and lifestyle modifications. You will also manage inventory and supplies for the vascular lab, ensure compliance with health and safety regulations, and participate in research and development projects to enhance vascular diagnostic techniques and patient outcomes.

Qualifications and Experiences:

• Degree in Vascular Science or related field
• HCPC registration
• Extensive experience in vascular diagnostics
• Proficiency in duplex ultrasound scans of the carotid arteries, peripheral arteries, and veins
• Strong communication and interpersonal skills
• Ability to work independently and as part of a team
• Attention to detail and accuracy in recording test results
• Familiarity with the latest vascular diagnostic equipment and techniques
• Experience in quality assurance and clinical audit processes
• Ability to train and supervise junior staff
• Knowledge of health and safety regulations in a clinical setting
• Commitment to continuous professional development and staying updated with advancements in the field

Why work with Pulse? 

From the moment you register with us, our focus is entirely on you. During our first conversation, you’ll quickly see that we understand your specialty inside and out. 

Our expert recruitment consultants are dedicated to finding you the best opportunities and supporting you every step of the way to secure the perfect placement. With our preferred or sole supplier status with many clients, you’ll have access to exclusive opportunities that you won’t find anywhere else. 

We always prioritize your best interests, engaging in meaningful conversations and truly listening to you. You are an individual, a professional—not just a resource. 

Reasonable Adjustments:

If you consider yourself to have a disability or require any reasonable adjustment during the recruitment process or within the workplace, please highlight this at the earliest opportunity by contacting our team. With this information, we will provide appropriate support to you throughout the process and into your work placement. 

We are unable to support or accept applications from candidates who are residents within the Red or Amber list of the Code of practice for the international recruitment of health and social care personnel in England, based on the World Health Organisation (WHO) Workforce Support and Safeguard List. 

Note: We are currently recruiting for multiple levels and positions, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.
• Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.
• Own Research work-streams at different levels, depending on seniority.
• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
• Collaborate with colleagues beyond the research team to translate your models into production-ready code.
• Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.
• Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.
• Ability to scope and effectively deliver projects.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following:
  1. operator learning (neural operators), or other probabilistic methods for PDEs;
  2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;
  3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).
• >2 years of experience in a data-driven role in a professional industry setting (excluding post-doc positions), with exposure to:
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  • developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);
  • iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;
  • combining theoretical reasoning with empirical intuition to guide investigation;
  • formulating and running experiment pipelines to benchmark models and produce comparable results;
  • writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.
• Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

📍London or Barcelona | UK remote | 💰 £95,000 to £130,000 + Incentive Awards tied to your performance + Benefits| Technology - Data  

About our Data Science Teams:

We're looking for a Lead Data Scientist excited to help build the bank of the future. You'll have the opportunity to super charge our user engagement in 2026 and help us to build a bank that customers truly love.

At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over 11 million customers in the UK. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.

Enable Monzo to Make Better Decisions, Faster

We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.

How we hire

We are excited to be expanding and are hiring for multiple roles across our Data Science teams! Whether your interests lie in Borrowing, Growth, Payments, Fincrime, Wealth, or Core, we are looking for talented individuals with a versatile skill set to contribute across our squads. While we allocate teams after the interview process, we aim to match your skills and aspirations with the most suitable role. Throughout the process, you will meet team members from across our Data Science collectives, who will guide you through the opportunities available. Join us and be part of shaping our future!

What you’ll be working on:

• Lead the data strategy and continue to evolve Monzo for our customers to make it magically simple to manage money day-to-day
• Develop and execute best practices for experimentation enabling our team to make data informed decisions
• Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices.
• Work closely with leaders in product, engineering, design and research to build and iterate on product ideas 

You should apply if:

• You enjoy working with cross functional fast moving teams
• You are able to think strategically about commercial products and how decisions using data can unlock more value for our customers
• You are excited about mentoring other data scientists and analytics engineers 
• You are excited by experimentation and utilising new data techniques to solve challenging problems 
• You want to understand the nuances of our data and are excited about laying the key foundational knowledge for our new products and features
• You are opinionated about how to think about measuring success and are willing to challenge the status quo

The interview process:

Our interview process involves: 

• Recruiter Call
• Initial Call 
• Technical assessment
• Final Interviews
• Business Fit/Collaboration
• Case Study
• Technical Interview

Our average process takes around 2-3 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process.

One of our recruiters has written a blog on the process, for extra details, hints and tips please see Data Hiring at Monzo

What’s in it for you:

💰 £95,000 to £130,000 + Incentive Awards tied to your performance + Benefits

✈️ We can help you relocate to the UK or Spain

✅ We can sponsor visas 

📍This role can be based in our London or Barcelona offices, but we're also open to distributed working within the UK (with ad hoc meetings in London).

⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.

📚Learning budget of £1,000 a year for books, training courses and conferences

➕And much more, see our full list of benefits here

If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.

#LI-NB2 #LI-Remote

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

Responsibilities

• Collaborate with engineers, designers, and product managers to solve ambiguous problems
• Research, prototype, and ship ML models into production
• Continuously improve existing algorithms and identify opportunities for new ones

What we Offer

• Office-based role in West London, four days a week with flexible start and finish times, plus one remote day of your choice
• Salary: £90,000 – £110,000
• Employee stock options plan
• Private medical and dental insurance
• Life and critical illness cover
• Latest-generation MacBook Pro and 4k display
• Monthly credit towards Wheely journeys
• Cycle to Work scheme
• Professional development stipend
• Relocation support, including visa sponsorship and allowance

Responsibilities

• Collaborate with engineers, designers, and product managers to solve ambiguous problems
• Research, prototype, and ship ML models into production
• Continuously improve existing algorithms and identify opportunities for new ones

What we Offer

• Office-based role in Nicosia, four days a week with flexible start and finish times, plus one remote day of your choice
• Competitive salary
• Employee stock options plan
• Private medical and dental insurance
• Daily Lunch allowance
• Latest-generation MacBook Pro and 4k display
• Professional development stipend
• Relocation support, including visa sponsorship and allowance

Note: We are currently recruiting for multiple levels and positions, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Own Research work-streams at a high-level to deliver outcomes.
  • Align priorities with problem stakeholders, internal and external.
  • Set the technical direction for the stream and apply judgement and taste to drive progress.
  • Plan roadmaps with clear milestones for key decisions and outcomes.
  • Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.
  • Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.
• Contribute towards Research group strategy and culture.
  • Identify research areas that would be valuable to the company and champion their development, ordering wrt other research objectives.
  • Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.
  • Nurture younger colleagues to grow their skillset and guide their professional development.
• The below activities in particular.
  • Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.
  • Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.
  • Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
  • Collaborate with colleagues beyond the research team to translate your models into production-ready code.
  • Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.

What you bring to the table

• Ability to scope and effectively deliver projects.
• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following:
  1. operator learning (neural operators), or other probabilistic methods for PDEs;
  2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;
  3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).
• Ideally, >4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in:
  • building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch / CUDA, ideally with exposure to JAX, NumPy / SciPy), especially including deep learning applications;
  • developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);
  • iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;
  • combining theoretical reasoning with empirical intuition to guide investigation;
  • formulating and running experiment pipelines to benchmark models and produce comparable results;
  • writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.
• Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

Our work spans three interconnected areas: 

• Marketplace Execution: building the control systems, supply prediction models, and decisioning logic that enable buyers to execute their customized strategies efficiently and at scale.
• Marketplace Curation: developing recommendation systems and curation frameworks that help buyers construct customized inventory strategies balancing audience relevance, publisher quality, and scale.
• Inventory Science: designing the measurement frameworks and causal methods that quantify the impact of marketplace decisions on advertiser outcomes, and translate complex trade-offs into actionable insight. 

Responsibilities 

• Build and maintain control systems that dynamically allocate ad budgets across sell-side partners based on quality signals and performance targets. 
• Design and analyze experiments using causal inference methods to measure the impact of inventory decisions on advertiser KPIs, and develop the metrics that make those trade-offs visible and actionable. 
• Build the recommendation systems and curation frameworks that help buyers find supply that reaches their target audiences at scale and delivers on their campaign outcomes. 
• Develop time series models to anticipate supply volume shifts and help buyers and partners plan accordingly. 
• Partner with engineering, product, and business teams to translate research into scalable, production-ready systems that improve marketplace value for buyers and sellers.  
• Define the applied science roadmap for the team — identifying high-impact problems, scoping solutions end-to-end, and driving projects from research through production. 

Who You Are 

We're looking for a Staff Applied Scientist who thrives at the intersection of rigorous methodology and real-world systems. You are comfortable moving between statistical modeling, experiment design, and ML, and you know how to translate that work into scalable solutions that have a measurable impact on how billions of ad dollars are spent. You care about getting things right, and you're motivated by problems where the stakes are high and the data is complex. 

• Advanced degree in data science, statistics, machine learning, economics, applied math, computer science, or a related field
• 7+ years of experience in data science or 5+ years of experience with a PhD
• Experience of owning projects end-to-end (from research to productionization at scale)
• Strong grounding in machine learning, statistics, experimental design, causal inference, and metric development
• Experience with recommendation systems or ranking models
• Experience with large‑scale data processing (e.g., Spark, EMR, Databricks)
• Comfortable with practices that enable reproducible analyses and useful prototypes—clean code, version control, and code review 

Nice to Have 

• Experience in programmatic advertising, real-time auctions, or supply-side systems
• Familiarity with control theory, constrained optimization, or budget allocation systems
• Experience building or applying agentic AI workflows, including the use of LLMs for automation, decision support, or data-driven product features 

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Research Scientist in Science

Founded in 2014, InstaDeep is today an EMEA leader in decision-making AI products for the Enterprise, with headquarters in London, and offices in Paris, Berlin, Tunis, Lagos, Dubai, Cape Town and the USA. InstaDeep has been named among the Top 100 global AI startups for three consecutive years by CB Insights, as well as one of the 100 most promising B2B companies in Europe, by Sifted. We have created an environment that ensures a challenge by working closely with a broad spectrum of high-quality clients, pushing you to thrive in an environment that’s rarely tedious and always looking to push you to come up with outside-the-box solutions using cutting-edge technologies. In our mission to stay ahead of the curve, we are proud to partner with firms such as BioNTech SE, Google DeepMind, NVIDIA and Intel, and world-class universities such as MIT, Oxford, UCL, and Imperial College London. We are also an NVIDIA Elite Service Delivery Partner and Google Cloud Partner.

Are you a Research Scientist in Science? You will contribute to knowledge in different fields, and plan and conduct experiments to help expand the canon of the company's scientific knowledge.

If so then keep reading…. 

As a Research Scientist in Science, you’ll be a part of the Research department, 

The Research Scientist in Science must accomplish the following:  

• Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.
• Engage and assist in the identification of research directions
• Contribute to the design and implementation of models, tools and libraries to accelerate our research effort.
• Adapt neural network algorithms to deploy on supercomputing architectures to best exploit modern parallel environments 
• Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing. 
• Contribute to the team’s publication efforts.
• Bridge the gap between the research and product teams by integrating new fundamental research into applied projects. 

Requirements:  

• Ph.D. degree in Computer Science, Machine Learning or a related field.
• Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax.
• Experience in developing and debugging in Python3 or similar languages.
• Experience with high-performance computing methods and frameworks such as MPI, Ray (distribution on clusters of CPUs and accelerators)
• Experience in planning and conducting research works
• A demonstrated ability to successfully deliver high-quality research, including publishing scientific papers (ICLR, NeurIPS, ICML, etc).
• Excellent communication skills and collaborative spirit.

Nice to haves

• 2-5 years experience

• Software engineering experience demonstrated via previous work, and contributions to open source or coding competitions.
• Reinforcement Learning, Computer Vision, or Natural Language Processing experience.

Our Diversity, Equity, and Inclusion commitments

We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this by other than by joining our team? 

At present, we operate in a hybrid work model of two days mandatory a week in the office. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.

Right to work: Please note you will require the legal right to work in the location you are applying for. 

If you have any further questions please do not hesitate to contact us at: talent@instadeep.com

📍London or Barcelona | UK remote | 💰 £95,000 to £130,000 + Incentive Awards tied to your performance + Benefits| Technology - Data  

About our Data Science Teams:

We're looking for a Lead Data Scientist excited to help build the bank of the future. You'll have the opportunity to super charge our user engagement in 2026 and help us to build a bank that customers truly love.

At Monzo, we're building a bank that is fair, transparent and a delight to use. We’re growing extremely fast and have over 11 million customers in the UK. We’ve built a product that people love and more than 80% of our growth comes from word of mouth and referrals.

Enable Monzo to Make Better Decisions, Faster

We have a strong culture of data-driven decision making across the whole company. And we're great believers in powerful, real-time analytics and empowerment of the wider business. All our data lives in one place and is super easy to use. 90% of day-to-day data-driven decisions are covered by self-serve analytics through Looker which gives data scientists the head space to focus on more impactful business questions and analyses.

How we hire

We are excited to be expanding and are hiring for multiple roles across our Data Science teams! Whether your interests lie in Borrowing, Growth, Payments, Fincrime, Wealth, or Core, we are looking for talented individuals with a versatile skill set to contribute across our squads. While we allocate teams after the interview process, we aim to match your skills and aspirations with the most suitable role. Throughout the process, you will meet team members from across our Data Science collectives, who will guide you through the opportunities available. Join us and be part of shaping our future!

What you’ll be working on:

• Lead the data strategy and continue to evolve Monzo for our customers to make it magically simple to manage money day-to-day
• Develop and execute best practices for experimentation enabling our team to make data informed decisions
• Collaboratively set standards and work with data across Monzo, fostering knowledge sharing and continuously improving data practices.
• Work closely with leaders in product, engineering, design and research to build and iterate on product ideas 

You should apply if:

• You enjoy working with cross functional fast moving teams
• You are able to think strategically about commercial products and how decisions using data can unlock more value for our customers
• You are excited about mentoring other data scientists and analytics engineers 
• You are excited by experimentation and utilising new data techniques to solve challenging problems 
• You want to understand the nuances of our data and are excited about laying the key foundational knowledge for our new products and features
• You are opinionated about how to think about measuring success and are willing to challenge the status quo

The interview process:

Our interview process involves: 

• Recruiter Call
• Initial Call 
• Technical assessment
• Final Interviews
• Business Fit/Collaboration
• Case Study
• Technical Interview

Our average process takes around 2-3 weeks but we will always work around your availability. You will have the chance to speak to our recruitment team at various points during your process.

One of our recruiters has written a blog on the process, for extra details, hints and tips please see Data Hiring at Monzo

What’s in it for you:

💰 £95,000 to £130,000 + Incentive Awards tied to your performance + Benefits

✈️ We can help you relocate to the UK or Spain

✅ We can sponsor visas 

📍This role can be based in our London or Barcelona offices, but we're also open to distributed working within the UK (with ad hoc meetings in London).

⏰ We offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team.

📚Learning budget of £1,000 a year for books, training courses and conferences

➕And much more, see our full list of benefits here

If you prefer to work part-time, we'll make this happen whenever we can - whether this is to help you meet other commitments or strike a great work-life balance.

#LI-NB2 #LI-Remote

Job overview:  

The Clinical Scientist, Clinical Sciences will assist with the clinical development and scientific oversight of late stage clinical trials.

The role partners closely with Clinical Operations, Statistics, Data Management, Clinical Safety, Regulatory Sciences, and HEOR to deliver high-quality studies, enabling timely, compliant, and insight-driven decision making.

Location: Hybrid in our Soho London office or remote in the United Kingdom.

Reports to: Principal Clinical Scientist, Clinical Sciences.

Duration: Until the end of 2026.

Roles and responsibilities 
(Include but are not limited to): 

• Serve as the primary “point person” for assigned clinical research duties
• Support scientific oversight during study execution, supporting database design, medical monitoring, site initiation visits, protocol deviation review and clarification, and interpretation of clinical signals across programs
• Author and review participant-facing documents such as the informed consent form and advertisement material
• Support development of study conduct and statistical analysis plans; review data to ensure quality of study conduct and data collection
• Accountable for compliance with ethical and scientific standards, regulatory requirements, and the Compass Quality Management System, ensuring participant safety, data integrity, and accuracy throughout the trial process
• Contribute to cross-functional readiness for key milestones (database lock, regulatory documents), establishing operating rhythms and documentation standards consistent with Compass values and governance
• Champion patient-centric design, incorporating feasibility data, KOL feedback, and ethical considerations into procedures, visit schedules, and burden-reduction strategies

Candidate Profile:

• A PhD or PharmD is highly preferred but not required. MS candidates with equivalent experience also will be considered
• PhD or post-doctoral training should be in neuroscience, pharmacology, psychology, psychiatry, or other relevant biomedical science
• PharmD graduates should have training in research methods or postdoctoral research experience as above
• MS graduates should demonstrate scientific accomplishment comparable to that acquired in doctoral training as above
• Relevant experience in conducting and designing clinical research in neuroscience, pharmacology, psychiatry, or neurology
• Proven capability to translate biology and patient insights into clear study objectives, endpoints, and operationally feasible designs
• Strong analytical and statistical skills, experience authoring scientific documents, and well-developed communication skills appropriate to varying target audiences
• Excellent scientific writing, data interpretation, and communication skills, with a track record of high-quality clinical documents and timely milestone delivery
• Mission-aligned, inclusive contributor who reflects Compass values and a wellbeing-first, stigma free culture

Role OVO-View

Team: Software Engineering

Location: Hub Based - Hybrid for all

Salary banding: £116,500 - 154,588

Experience: Expert

Working pattern: Full-Time

Reporting to: Director, Data & AI

Sponsorship: Unfortunately we are unable to offer sponsorship for this role.

This role in 3 words: Ownership, Innovative, Impactful

Top 3 qualities for this role: Communication, Leadership, Drive

Where you’ll work:

Depending on the needs of your business area, we expect hub based people to be in the office at least once a week, and to go to OVO Connection events in-person. 

You’ll be assigned to the  closest one of our three hub offices, Bristol, Glasgow, or London; unless your role requires field-based work. Each hub has accessible spaces to park your laptop, is designed to inspire people, help them connect and bring big ideas to life.

Everyone belongs at OVO:

At OVO, we are on a mission to solve one of humanity's biggest challenges, the climate crisis. And we know it takes all of us to change the world. That's why we need diverse people from all abilities, gender identities, ethnicities, ages, sexual orientations, life experiences and backgrounds to join us.

Teamworking for the planet:

Everything we do here spins around Plan Zero. So, naturally, the team you’ll be joining plays a gigantic role in making that happen. Here’s how:

You will be joining one of our Core AI teams, tackling issues central to OVO’s business and customer experience. We are building out new tools to support our back-office teams resolve customer bill issues more easily and swiftly. In our attempts we will be trialling the use of new AI capabilities to transform how our business operates and meets customer demands.

This role in a nutshell:

As a Principal Data Scientist you’ll play a key strategic role in shaping the future of our data science practice. You'll lead innovative, high-impact projects, define our technical direction, and champion best practices across the organisation. Working closely with cross-functional teams, you’ll drive forward research and experimentation to keep OVO at the forefront of data science, ensuring our work is not only cutting-edge but also aligned with our mission to build a more sustainable future.

Your key outcomes will be:

• Technical Leadership and Vision: Shape and communicate the technical direction of OVO’s data science function, guiding the team through expert mentorship and driving the adoption of modern tools, technologies, and approaches to elevate our capabilities.
  
  
• Leading Cutting-Edge Initiatives: Drive high-impact data science projects that solve complex business challenges and align with OVO’s strategic goals. Champion innovation and deliver scalable, forward-thinking solutions.
  
  
• Cross-Functional Collaboration: Work closely with engineering, product, and business teams to embed data science into products and decisions. Communicate insights clearly to diverse audiences and build trusted partnerships across the organisation.
  
  
• Defining Technical Strategy: Develop a strategic roadmap for data science, informed by emerging trends and evolving business needs. Identify areas for innovation and lead the continuous evolution of our data science practice.
  
  
• Driving Research Initiatives: Lead research into advanced techniques and applications, publishing findings and representing OVO at industry events. Grow a culture of experimentation and learning within the team.
  
  
• Ensuring Best Practices: Establish standards for model development, validation, and deployment while ensuring data quality, compliance, and security. Promote scalable, reliable infrastructure and ethical data use.
  
  
• Community of Practice: Lead and grow the data science Community of Practice, sharing knowledge, mentoring peers, and contributing to learning pathways that support development and career growth across the team.

You’ll be a successful Principal Data Scientist at OVO if you…

• Proven ability to lead complex, high-impact data science initiatives that drive strategic outcomes
• Deep expertise in advanced machine learning, statistical methods, and algorithm development
• Proficient in Python or R, and advanced SQL, with strong research and analytical skills
• Demonstrated experience evaluating and applying emerging tools, technologies, and methodologies
• Skilled in defining and executing data science strategies aligned with business objectives
• Strong communicator, able to clearly explain technical concepts to diverse technical and non-technical audiences
• Effective collaborator with cross-functional teams, building trusted relationships across the organisation
• Recognised for technical leadership, mentorship, and fostering a culture of continuous innovation
• Committed to best practices in data science, ensuring quality, compliance, and scalable infrastructure

Let’s talk about what’s in it for you:

We keep our pay ranges broad on purpose to give us, and you, flexibility to match your experience to our zero carbon mission.

You’ll be eligible for an on-target bonus of 15%. We have one OVO bonus plan that focuses on the collective performance of our people to deliver our Plan Zero goal. 

We also offer plenty of green benefits and progressive policies to help you feel like you belong at OVO…and there’s flex pay. We'll give you 9% Flex Pay on top of your salary – 4% of this is auto enrolled into your pension, and the remaining 5% is yours to do what you like with. You can use this to buy from our extensive range of flexible benefits, including our green benefits which we've put at the heart of our offering, add to your pension or even take it as cash.

Here’s a taster of what’s on offer: 

For starters, you’ll get 34 days of holiday (including bank holidays).

For your health
With benefits like a healthcare cash plan or private medical insurance depending on your career level, critical illness cover, life assurance, health assessments, and more

For your wellbeing
With gym membership, travel insurance, workplace ISA, will writing services, dental insurance, and more

For your lifestyle
With extra holiday buying, discount dining, home & tech loans, and supporting your favourite charities with give-as-you-earn donations

For your home 
Get up to £400 towards any OVO Energy plan, plus great discounts on solar, smart thermostats and EV chargers

For your commute
Nab a great deal on ultra-low emission car leasing, plus our cycle to work scheme and public transport season ticket loans

Want to hear about our full range of flexible benefits and progressive people policies? Our People Team can tell you everything you need to know.

For your Belonging

To find better ways to support our people, we need to listen to each other’s experiences and find ways to build a truly inclusive and diverse workplace. As part of this, we have 8 Belonging Networks at OVO. Led by our people, for our people - so when you join OVO, you can play a part - big or small - with any of the Networks. It's up to you.

Oh, and one last thing...

We’d be thrilled if you tick off all our boxes, yet we also believe it’s just as important we tick off all of yours. And if you think you have most of what we’re looking for but not every single thing, go ahead and hit apply. We’d still love to hear from you!

If you have any additional requirements, there’s a space to let us know on the application form; we want to make the process as easy and comfortable for you as possible.

Join Heartflow’s world-class Research team as a Collaborating Research Scientist with a joint visiting researcher appointment in Professor Ben Glocker’s lab at Imperial College London. This position focuses on advancing state-of-the-art Generative AI technologies for Coronary Computed Tomography Angiography (CCTA). In this role, you will work on cutting edge academic research, IP generation and high-impact publications while ensuring that technical breakthroughs can be translated into Heartflow’s product-grade models.

At Imperial College: You will be an active member of one of the world’s leading medical imaging labs, participating in seminars, collaborating with academics, and engaging in the vibrant Imperial ecosystem in South Kensington.

At Heartflow: You will be a key stakeholder in our research roadmap, with access to massive, proprietary datasets that are unavailable to pure academic labs, with the opportunity for translation of your work into medical devices with global impact.

Key Responsibilities:

• Design and implement state-of-the-art generative architectures to synthesize high-fidelity, anatomically accurate CCTA image data.
• Publish and present at top-tier venues (such as MICCAI, ICCV, CVPR, NeurIPS).
• Provide technical reports and reproducible code to enable the translation of research into products by Research team members and development teams.
• Identify and protect new IP for Heartflow in emerging AI domains.
• Educate people across groups and departments on generative AI.

Skills Needed:

• Proven expertise in generative AI methods for computer vision or medical image analysis (diffusion models, flow matching, GANs, VAEs).
• Ability to clearly communicate complex ideas, tailoring content for diverse audiences.
• Experience developing generative AI systems with large-scale imaging datasets.
• Advanced proficiency in Python and PyTorch, with a commitment to writing clean, reproducible and scalable research code.
• A track record of first-author publications in top tier AI or medical imaging conferences. 

Desirable Skills:

• Experience in causal modeling, and/or conditional generative models.
• Experience in developing multimodal generative AI systems.
• Experience developing AI systems with sparse and/or noisy labels.
• Experience building deep learning models for 3D medical image data.

Educational Requirements & Work Experience:  

• A PhD degree in computer science, engineering, math or similar technical field. 
• Preferably 2+ years related experience, in industry or academia, with Generative AI in computer vision or medical image analysis. 

#LI-IB1 

What's the opportunity? 

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What will I be doing? 

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What skills do I need? 

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated. 
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What will I be doing? 

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What skills do I need? 

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

• The Research, Analytics & Data Science (RAD) team at Intercom use data and insights to drive evidence based decision-making. We're a team of data scientists and product researchers who use data — both big and small — to unlock actionable insights about our customers, our products and our business. We generate insights that build customer empathy, drive product strategy and shape products that deliver real value to our customers. If you get really excited about asking the right questions, exploring patterns in data and surfacing actionable insights that drive strategic decisions, then this role is for you.
• Data Scientists in RAD partner with teams across R&D to help Intercom make sense of our users, our products and our business, using metrics and data. This role will enable you to drive key data projects that directly impact our customers and millions of end users who communicate via our messaging platform daily.

What will I be doing? 

• You’ll partner with product teams to help them identify important questions and answer those questions with data
• You’ll work closely with product managers, designers and engineers to develop key product success metrics, to set targets, to measure results and outcomes, and to size opportunities
• You’ll design, build and update end-to-end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables.
• You’ll partner closely with product researchers to build a holistic understanding of our customers, our products and our business.
• You’ll influence our product roadmap and product strategy through experimentation, exploratory analysis and quantitative research
• You’ll build and automate actionable models and dashboards
• You’ll craft data stories and share your findings and recommendations across R&D and the broader company
• You’ll drive and shape core RAD foundations and help us improve how the RAD org operates

What skills do I need? 

• 5 + years experience working with data to solve problems and drive evidence-based decisions
• Excellent SQL skills and experience of  applying analytical and statistical approaches to problem solving
• Proven track record of initiating and delivering actionable analysis and insights that drives tangible impact with minimal supervision
• Excellent communication skills (technical and non-technical) and a focus on driving impact
• Strong growth mindset and sense of ownership. Innate passion and curiosity
• Experience with a scientific computing language (such as R or Python)

Bonus skills & attributes 

• Experience with BI/Visualization tools like Tableau, Superset and Looker
• Experience with data modeling and ETL pipelines
• Experience working with product teams
• Experience leveraging AI tools to boost efficiency and creativity across the data science workflow — from ideation and coding to analysis and communication

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

Intercom’s Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

What will I be doing? 

• Play an active role in hiring, mentoring and career development of other engineers

• Raise the bar for technical standards, performance, reliability, and operational excellence

• Identify areas where ML can create value for our customers

• Identify the right ML framing of product problems - Working with teammates and Product and Design stakeholders

• Conduct exploratory data analysis and research - Deeply understand the problem area

• Research and identify the right algorithms and tools - Being pragmatic, but innovating right to the cutting-edge when needed

• Perform offline evaluation to gather evidence an algorithm will work

• Work with engineers to bring prototypes to production

• Plan, measure & socialize learnings to inform iteration

• Partner deeply with the rest of team, and others, to build excellent ML products

What skills might I need? 

• 5-8 years applied ML experience

• Previous background in a senior/staff role (data science, software development or academic)

• Significant, demonstrated impact that your work has had on the product and/or the teams

• Strong programming skills

• Experience as the primary technical leader for a team

• Strong communication skills, both within engineering teams and across disciplines.

• Comfort with ambiguity

• Typically have advanced education in ML or related field (e.g. MSc)

• Scientific thinking skills

Bonus skills & attributes 

• Track record shipping ML products

• PhD or other experience in a research environment

• Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering

• Strong stats or math background

• Visualization, data skills, SQL, matplotlib, etc.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us!

• Competitive salary and equity in a fast-growing start-up

• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

• Regular compensation reviews - we reward great work!

• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

• Open vacation policy and flexible holidays so you can take time off when you need it

• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too 

• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated

We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organisation. We're committed to an inclusive and diverse Intercom! We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

What's the opportunity? 

• The Research, Analytics & Data Science (RAD) team at Intercom use data and insights to drive evidence based decision-making. We're a team of data scientists and product researchers who use data - both big and small -  to unlock actionable insights about our customers, our products and our business. We generate insights that build customer empathy, drive product strategy and shape products that deliver real value. If you get excited about asking the right questions, exploring patterns in data and turning insights into action, this role is for you..
• Data Scientists in RAD partner with teams across R&D to help Intercom make sense of our users, our products and our business, using metrics, data and analysis. This role will enable you to drive key data projects that directly impact our customers and millions of end users who communicate via our messaging platform daily.

What will I be doing? 

• You’ll partner with product teams to help them identify important questions and answer those questions with data
• You’ll work closely with product managers, designers and engineers to develop key product success metrics, to set targets, to measure results and outcomes, and to size opportunities
• You’ll design, build and update end-to-end data pipelines, working closely with stakeholders to drive the collection of new data and the refinement of existing data sources and tables.
• You’ll partner closely with product researchers to build a holistic understanding of our customers, our products and our business.
• You’ll influence our product roadmap and product strategy through exploratory analysis and quantitative research

Increasingly, you will also:

• Use AI-assisted tools (e.g. Claude Code, Cursor) to accelerate analysis, coding and insight generation
• Identify opportunities to automate your own workflows and reduce time spent on repetitive tasks
• Build scalable data products (dashboards, models, internal tools) that enable stakeholders to self-serve insights
• Help teams interact more directly with data (e.g. through better abstractions, semantic layers, or AI-powered interfaces)
• Raise the bar for how AI is used within RAD- sharing patterns, workflows and best practices
• Craft clear, compelling data stories and communicate recommendations across R&D and the broader company
• Contribute to and shape core RAD foundations, improving how the team operates

What skills do I need? 

• 5 + years experience working with data to solve problems and drive evidence-based decisions
• Strong SQL skills and solid grounding in statistics
• Experience working closely with product teams
• Proven track record of delivering actionable insights that drive measurable impact with minimal supervision
• Strong product intuition, business acumen and ability to connect analysis to strategy
• Excellent communication skills (technical and non-technical), with a focus on driving decisions and outcomes
• Strong ownership, curiosity and growth mindset
• Experience with a scientific computing language (e.g. Python)

And increasingly important:

• Ability to effectively use AI tools (e.g. Claude Code, Cursor) to accelerate and improve your work
• A mindset of automation and leverage - looking for ways to scale your impact beyond one-off analyses
• Comfort working in ambiguous, fast-evolving environments where tools and workflows are rapidly changing

Bonus skills & attributes 

• Experience with data modeling and ETL pipelines (esp dbt)
• Experience building internal tools, data products or self-serve analytics capabilities
• Experience leveraging AI across the data workflow - from ideation and coding to analysis and communication

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated. 
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

The Research, Analytics & Data Science (RAD) team turns insight into action. We uncover customer, product, and business insights and translate them into tools and decision systems embedded directly into GTM workflows.

AI has unlocked an entirely new generation of internal tools for our GTM teams. We’re evolving from static dashboards to LLM and agent-powered workflows that do the work: auto-researching accounts, summarizing prior interactions, drafting personalized outreach, flagging renewal risk, and assembling decks and docs - enabling Sales and Success to focus on high-value conversations.

The RAD team partners closely with GTM Systems to define problems, solutions, and measure impact - from prototype to production.

This is a high-ownership role for someone who thrives in ambiguity, is energized by solving complex real-world problems, and is motivated by seeing their work translate into tangible business impact.

What will I be doing? 

• Design, evaluate, and ship AI-powered internal tools for GTM use cases - including account research & summaries, next-best-action recommendations, renewal propensity, pipeline risk detection, QBR/autobrief generation, and post-call summarization & follow-ups.
• Work end-to-end: Own the full lifecycle, from problem definition and data modeling to building production-ready tools, including writing Python backends and React frontends.
• Prototype fast, ship to learn: Rapidly build with users, then productionize quickly to iterate and deliver impact.
• Instrument for adoption and outcomes: Define success through real usage and measurable business impact (e.g., improved win rate, conversion, expansion).
• Evangelize and enable: Document playbooks, run enablement sessions, and help leaders operationalize new tooling across teams.

What skills do I need? 

• Proven track record of applied data science with measurable GTM impact - you’ve shipped models or tools that moved metrics like conversion, cycle time, or retention.
• LLM/ML application experience - familiarity with RAG, prompt and tool design, vector search, evals and have leveraged AI for development.
• Excellent SQL skills and fluency in Python or R, with experience applying analytical and statistical methods to business problems.
• Experience with orchestration tools (e.g., DBT, Airflow) for deploying reliable data workflows.
• Strong communication and empathy - ability to translate complex data concepts for non-technical stakeholders.
• Collaborative product mindset - comfort working closely with Sales and Success teams to turn ambiguity into clear deliverables.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
• Regular compensation reviews - we reward great work
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
• Open vacation policy and flexible holidays so you can take time off when you need it
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

#LI-Hybrid

What's the opportunity? 

Intercom’s Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

What will I be doing? 

• Identify areas where ML can create value for our customers

• Identify the right ML framing of product problems

• Working with teammates and Product and Design stakeholders

• Conduct exploratory data analysis and research

• Deeply understand the problem area

• Research and identify the right algorithms and tools

• Being pragmatic, but innovating right to the cutting-edge when needed

• Perform offline evaluation to gather evidence an algorithm will work

• Work with engineers to bring prototypes to production

• Plan, measure & socialize learnings to inform iteration

• Partner deeply with the rest of team, and others, to build excellent ML products

What skills might I need? 

• Broad applied machine learning knowledge

• 3-5 years applied ML experience

• Practical stats knowledge (experiment design, dealing with confounding etc)

• Intermediate programming skills

• Strong communication skills, both within engineering teams and across disciplines.

• Comfort with ambiguity

• Typically have advanced education in ML or related field (e.g. MSc)

• Scientific thinking skills

Bonus skills & attributes 

• Track record shipping ML products

• PhD or other experience in a research environment

• Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering

• Strong stats or math background

• Visualization, data skills, SQL, matplotlib, etc.

Benefits 

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

• Competitive salary and equity in a fast-growing start-up

• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

• Regular compensation reviews - we reward great work!

• Pension scheme & match up to 4%

• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

• Flexible paid time off policy

• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too 

• MacBooks are our standard, but we’re happy to get you whatever equipment helps you get your job done

• Relocation support for those moving to our offices

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our AI team is a central R&D group comprised of quantitative researchers, engineers, and ML experts leading LLM research and applications at Jump. Our mission is to combine emerging techniques and models with original research to generate signals from unstructured data.

What You’ll Do: 

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of leading an open-ended research project from concept to production: finding compelling problems well suited to current and projected LLM capabilities, collaborating extensively with trading teams to understand requirements and constraints, and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research process with the potential for firmwide application. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, and market intuition, and welcome all candidates who can demonstrate brilliance in one area, competence in a second, and enthusiasm for the third.

Other duties as assigned or needed.

Skills You’ll Need:

• 5+ year track record of creating ML systems with real metrics & impact in industry and/or academia
• Strong general ML background with some exposure to language modeling architectures (e.g. transformers, SSMs)
• Solid development skills in Python and/or C++
• Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX
• Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Reliable and predictable availability

Bonus Points

• Experience with HPC and distributed large model training
• Experience with GPU performance optimization (CUDA or ROCm)
• Experience with end-to-end model development, especially in LLMs
• Prior academic publications and/or contributions to open-source AI research
• Strong opinions on best practices in ML research, tooling, and/or infrastructure

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

The quantitative trading teams at Jump Trading probe and examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis, machine learning and deep learning skills, using the results of their research to make forecasts and develop profitable predictive trading models.

What You’ll Do: 

We are seeking research scientists with a demonstrated ability to apply deep learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.

Other duties as assigned or needed.

Skills You’ll Need:

• 5+ years of experience in developing DL systems with measurable impact in industry and/or academia
• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
• Proficiency in Python and/or C++
• Strong foundation in mathematics and statistics
• Ability to thrive in a collaborative, team-oriented environment
• PhD, or Master's degree in Computer Science, Mathematics, (or related subject)
• Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent
• Reliable and predictable availability
• Excellent written and verbal communication skills in English

About the role:

You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.

Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. For the London team, we are opportunistically hiring for the following research areas:

• AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
• Alignment Stress-testing: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.

Note: Currently, the team's hub is in San Francisco, so we require all candidates to be based at least 25% in London and travel to San Francisco occasionally. Additionally, we are prioritizing growing our San Francisco teams, so you may not hear back on your application to the London team unless we see an unusually strong fit. For this role, we conduct all interviews in Python.

Representative Projects:

We’re looking for a talented Senior Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers and suppliers.

Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed across insight automation and product assortment, with applications of science including identifying new and growing product needs, optimising the mix of products, predicting the impact of changes, product attribute generation and applications of generative AI for product support and insights.

What you'll be doing:

• Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
• Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data.
• Perform exploratory data analysis to characterise and visualise datasets 
• Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
• Help identify new opportunities within the Data Science space for future dunnhumby solutions.
• Implement advice from colleagues to resolve challenges.
• Follow Quality Assurance processes, ways of working and meet coding standards.
• Ensure smooth running of your projects, working with senior team members for direction.
• Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who you’ll get to work with:

• Within dunnhumby you’ll primarily work with
• Applied and Research Data Scientist teams
• Data Science Engineering teams
• Product and Client teams where required

What you'll need:

• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries.
• Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL
• Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas and scikit-learn, along with data visualisation technologies.
• A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.

A plus if you also have:

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience in retail sector.

We’re looking for a talented Research Data Scientist who expects more from their career. It’s a chance to extend and improve dunnhumby’s world class science capabilities. It’s an opportunity to work with a market-leading business to explore new opportunities for us and influence global retailers and suppliers.

Joining our team, you’ll work with world class and passionate people to apply machine learning and statistical techniques to business problems. You’ll contribute to the research and implementation of new approaches to address complex problems and perform data analysis and model validation. You’ll have the opportunity to present results to a variety of internal stakeholders and will apply these techniques and algorithms to create dunnhumby science solutions that can be delivered across our clients and engineered into science modules.

This role will be focussed across insight automation and product assortment, with applications of science including identifying new and growing product needs, optimising the mix of products, predicting the impact of changes, product attribute generation and applications of generative AI for product support and insights.

What you'll be doing:

• Create new science-based solutions that can be captured as science modules and applied across clients, with support from senior team members.
• Pick up new machine learning approaches, such as regularised regression, clustering or tree-based ensembles, graph-based approaches, natural language processing and neural network techniques and apply them on client data.
• Perform exploratory data analysis to characterise and visualise datasets 
• Extend and develop programming skills, in languages such as Python and Spark, to develop efficient science code for science modules.
• Help identify new opportunities within the Data Science space for future dunnhumby solutions.
• Implement advice from colleagues to resolve challenges.
• Follow Quality Assurance processes, ways of working and meet coding standards.
• Ensure smooth running of your projects, working with senior team members for direction.
• Build strong relationships within the team and with internal stakeholders, ensuring clear and effective communication.

Who you’ll get to work with:

• Within dunnhumby you’ll primarily work with
• Applied and Research Data Scientist teams
• Data Science Engineering teams
• Product and Client teams where required

What you'll need:

• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience with machine learning techniques such as regularised regression, clustering or tree-based ensembles, and the ability to implement them through libraries.
• Experience with programming, ideally Python, and the ability to quickly pick up handling large data volumes with modern data processing tools, e.g. by using Hadoop / Spark / SQL
• Experience with or ability to quickly learn open-source software including machine learning packages, such as Pandas and scikit-learn, along with data visualisation technologies.
• A willingness to present your work to both technical and non-technical audience and to contribute to the wider data science community.

A plus if you also have:

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Statistics, Physics, Engineering, Biology or related field.
• Experience in retail sector.

About the role

Anthropic is seeking a Research Engineer/Scientist to join the Science of Scaling team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. You'll contribute across the entire stack, from low-level optimizations to high-level algorithm and experimental design, balancing research goals with practical engineering constraints.

Responsibilities:

• Conduct research intro the science of converting compute into intelligence
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyze scientific experiments to advance our understanding of large language models
• Optimize training infrastructure to improve efficiency and reliability
• Develop dev tooling to enhance team productivity

You may be a good fit if you:

• Have significant software engineering experience and a proven track record of building complex systems
• Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Are proficient in Python and experienced with deep learning frameworks
• Are results-oriented with a bias towards flexibility and impact
• Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team
• View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximize impact
• Care about the societal impacts of your work and have ambitious goals for AI safety and general progress

Strong candidates may have:

• Experience with JAX
• Experience with reinforcement learning
• Experience working on high-performance, large-scale ML systems
• Familiarity with accelerators, Kubernetes, and OS internals
• Experience with language modeling using transformer architectures
• Background in large-scale ETL processes
• Experience with distributed training at scale (thousands of accelerators)

Strong candidates need not have:

• Experience in all of the above areas — we value breadth of interest and willingness to learn over checking every box
• Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well
• An advanced degree — exceptional engineers with strong research instincts are equally encouraged to apply

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role

Data Scientists bridge the gap between raw data and predictive modelling. We believe everything starts with data. You will work closely with our quantitative research team, applying advanced techniques to engineer, validate, and refine features that feed directly into our systematic models. This is a role within an established investment team, offering opportunities for progression into more senior research responsibilities across the full trading pipeline.

Responsibilities

• Conduct thorough data analysis under the mentorship of a senior quantitative researcher.
• Generate novel ideas for enhanced proprietary data products.
• Track and evaluate new offerings from internal and external data vendors in partnership with Compliance.
• Transform firm approved raw datasets into robust features for our systematic models.
• Build analytical tools to supplement our shared research framework.

Requirements

• BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline.
• Programming in Python (or a comparable language) and working knowledge of SQL.
• Strong analytical and quantitative skills.
• Willingness to take ownership of their work.
• Ability to work both independently and collaboratively within a team.
• Strong desire to deliver high quality results in a timely fashion.
• High attention to detail.
• Prior experience as a data analyst, data sourcing specialist, or data scientist for a financial firm is a plus
• Commitment to the highest ethical standards.

The role

Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention.

As a Senior Data Scientist within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network.

At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale.

What you’ll do

• Lead the end-to-end delivery of models at scale, from initial discovery and feature engineering to production, A/B testing and continuous monitoring.
• Collaborate with product and engineering peers to turn complex data into real-time, mission-critical fraud prevention solutions.
• Raise the team’s collective bar through hands-on technical leadership and knowledge sharing.
• Proactively research and integrate latest developments in ML and payer fraud prevention to drive innovation at GoCardless.

What excites you

• Being a self-starter who thrives on taking a vague business problem and owning the journey from the first prototype to a live, measurable solution.
• An opportunity to introduce and scale advanced architectures to solve high-stakes fraud and payment challenges.
• Moving beyond execution to help define the technical roadmap for Payer Fraud Prevention, ensuring we leverage the best tools for the job.
• Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.

What excites us

• You hold a degree (or PhD) in a STEM discipline or an equivalent commercial experience.
• You bring hands-on experience with sophisticated architectures, such as deep learning, graph-based, or sequence-based models (experience in Fintech, Fraud Prevention, or Payments is a big plus).
• You can translate complex ML concepts into practical product solutions and communicate these ideas clearly to non-technical peers.
• You are comfortable owning the full lifecycle, from deep-dive analysis and feature engineering to prototyping, validation, and live A/B testing.
• You lead by example, writing clean, high-quality code and raising the team’s technical bar through knowledge sharing and code best practices.

The role

Fraud prevention is an ever-evolving puzzle, making it one of the most rewarding and impactful areas in fintech. At GoCardless, our Fraud Prevention team develops the intelligent systems that protect our platform, our merchants, and their customers.

As a Senior Data Scientist, you will guide the design and delivery of models that operate in real time across our global payment network. You’ll work at the intersection of machine learning, graph-based detection, and behavioural modelling to stay ahead of changing patterns turning research into production systems that make a tangible difference in the fight against financial crime.

You’ll collaborate closely with Engineers, Fraud Analysts, and Product Managers to help shape the technical roadmap as we expand into new markets. Our stack is centred around Google Cloud Platform and Vertex AI, using Python, SQL, and BigQuery to build and support high-performance models at scale.

What you'll do

• Contribute to the full model lifecycle, from initial discovery and feature engineering through to production, experimentation, and continuous monitoring.
• Design and refine real-time ML systems that reduce false positives and ensure a smooth, secure experience for legitimate customers.
• Foster a responsive feedback loop, adapting models as patterns evolve to ensure our defences remain robust and effective.
• Help shape the technical direction of fraud prevention ML at GoCardless, exploring new approaches as we grow globally.
• Support the team’s growth through technical mentorship, knowledge sharing, and a commitment to high-quality code.

What excites you

• Solving complex, dynamic problems: Developing systems that can adapt and respond to changing environments.
• End-to-end ownership: Seeing a project through from a conceptual business need to a live, impactful solution.
• Strategic influence: Contributing to the ML roadmap and helping determine what we build next, rather than just how we build it.
• Holistic Data Science: Engaging in deep-dive analysis, prototyping, and live experimentation.
• Modern Infrastructure: Building production-grade models on GCP and Vertex AI, with the flexibility to explore advanced architectures.

What excites us

• You hold a degree (or PhD) in a STEM discipline, or bring equivalent depth through commercial experience.

• You have hands-on experience with modelling approaches such as deep learning, graph-based methods, or sequence models. While fintech experience is great, we value transferable skills from fields like cybersecurity or risk modelling.
• You have a track record of deploying models in production that create measurable value.
• You can translate complex ML concepts into clear, practical solutions for stakeholders across the business.
• You enjoy writing clean code and helping the team thrive through thoughtful reviews and shared learning.

Base salary range: £99,200 - £148,800

Base salary ranges are based on role, job level, location, and market data.  Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work.