data engineer

data scientist

machine learning engineer

senior data scientist

senior data engineer

data scientist deep learning practitioner

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Reporting to: Re &amp; ILS Head of Data
 
 
 
 
 Location:
 
 London
 
 
 Type: Permanent
 
 
 
 Role Overview
 
 
 
 The Lead Data Scientist is a crucial member of the
 
 extended
 
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 
 Data Science and Machine Learning
 
 chapter.
 
 
 This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).
 
 
 You will co-lead the new Data Science chapter with the RE&amp;ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&amp;ILS strategic Value Streams. Whilst the chapter grows, you are expected to be
 
 hands-on
 
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 
 
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 
 Group AI Governance Framework
 
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 
 
 This is likely to be your first managerial role and the first time you have had one or more direct reports &ndash; having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders &ndash; Head of Data and the Hiscox Group Head of Data Science as well.
 
 
 
 About Hiscox Re &amp; ILS
 
 
 
 Hiscox Re &amp; ILS is located in
 
 Bermuda and London
 
 and underwrites reinsurance risks from around the world on behalf of our own and other people&rsquo;s capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Chapter Leadership &amp; Talent Management
 </li>
 <li>
 People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture.
 </li>
 <li>
 In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths.
 </li>
 <li>
 Culture &amp; Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members.
 </li>
 <li>
 Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice.
 </li>
 <li>
 Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn &ndash; especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value.
 </li>
 <li>
 Solution Delivery &amp; ML Ops Excellence
 </li>
 <li>
 Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions.
 </li>
 <li>
 ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour.
 </li>
 <li>
 Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast &ndash; as a lot of AI use cases will be highly experimental in nature with no guarantees of success.
 </li>
 <li>
 Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models.
 </li>
 <li>
 Strategy, Governance &amp; Innovation
 </li>
 <li>
 Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains.
 </li>
 <li>
 Governance &amp; Compliance: Champion data and model governance, working within the Group AI Governance Framework. Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work.
 </li>
 <li>
 Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&amp;D to deliver reliable insights and potential next steps quickly.
 </li>
 <li>
 Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership.
 
 
 
 </li>
 </ul>
 
 Required Experience And Structure
 
 
 
 <ul>
 <li>
 Reporting: Reports into the RE&amp;ILS Head of Data with a dotted line into the new Group Head of Data Science.
 </li>
 <li>
 Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&amp;ILS Data Science Chapter.
 </li>
 <li>
 Key Partners: RE&amp;ILS CTO, Group Head of Data Science, RE&amp;ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft).
 
 
 
 </li>
 </ul>
 
 Candidate Profile
 
 
 
 The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards. You will have a strong determination and resilience and not fear failure or the inevitable setbacks often found in highly experimental work.
 
 
 
 Main Experience Required Is
 
 
 
 <ul>
 <li>
 Deep Interest in Leadership: As an experienced data scientist or machine learning engineer, has previously demonstrated excellent traits in mentoring and coaching more junior team members and has been happy to invest in them - clearly demonstrating they care about other peoples&rsquo; career progression. Also you can evidence some successful business outcomes that you personally drove forward using advanced Data Science/AI &ndash; as this most likely is your first leadership role.
 </li>
 <li>
 Technical Depth: Extensive "hands-on" experience in architecting, designing, and building complex ML models, with a strong understanding of cloud services and the AI/ML/LLM ecosystem.
 </li>
 <li>
 ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
 </li>
 <li>
 AI and Data Governance: Mature understanding of AI and Data governance - data obfuscation &amp; data privacy laws, data version control, data lineage, and the application of AI governance frameworks in a regulated environment.
 </li>
 <li>
 Stakeholder Management: Experience in managing and driving collaboration with business unit leaders (Underwriters, pricing teams, MI team) and external technology partners like Google Cloud, Snowflake, DataIku and Microsoft.
 </li>
 <li>
 Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
 </li>
 <li>
 Capacity for independent, high-quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill-defined and challenging business problems.
 </li>
 <li>
 Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures.
 </li>
 <li>
 Real world experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), AI Agents and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.
 </li>
 <li>
 Demonstrate a Solid understanding of foundational statistics and experimental design. Pioneer the development and robust deployment of highly impactful machine learning and AI-driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization.
 </li>
 <li>
 Ability to translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real-world adoption and beneficial outcomes of our analytical work.
 </li>
 <li>
 Ability to elevate the technical maturity and capabilities of the data science chapter by shaping and implementing industry-leading AI, data, and analytics techniques, methodologies, and engineering best practices.
 </li>
 <li>
 Educator: shown the ability to train and coach more junior and mid-level team members - ensuring they have excellent career progression and become high performers.
 
 
 
 </li>
 </ul>
 If you are a visionary expert looking for your first leadership role and ready to accelerate our value delivery and champion all things Data Science and AI, we invite you to apply for the position of Lead Data Scientist at Hiscox Re &amp; ILS. Join our team and be a catalyst for AI adoption in a dynamic, forward-thinking organization.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Lead Data Scientist

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
We are hiring a Lead Data Scientist to drive the technical delivery of our most demanding AI engagements and to lead a growing team of data scientists and AI engineers. This role is for a practitioner who is equally fluent in the rigour of traditional data science (statistical modelling, machine learning, experimentation) and the fast-moving world of large language models and agentic AI. You understand that the best solutions often combine both.
You will own delivery from problem framing through to deployment, ensuring the work is technically sound, commercially valuable, and aligned to the architectural vision. As a lead, you will mentor the team, raise engineering and modelling standards, and act as a trusted technical partner in client conversations. You will help clients see not just what is possible, but what is practical and worth doing.
This is a delivery-focused leadership role with genuine breadth: one week you might be tuning a forecasting model, the next designing an agentic workflow or evaluating an LLM pipeline for a client pilot.
Required skills &amp; experience:<ul><li>
Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.</li><li>
Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.</li><li>
Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.</li><li>
Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.</li><li>
Ensure best practice across the AI lifecycle &mdash; experimentation, evaluation, testing, deployment, and monitoring.</li><li>
Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.</li><li>
Support pre-sales and client discussions with credible technical input and realistic estimation.</li><li>
Champion reproducibility, model governance, and responsible practice in everyday delivery.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.</li><li>
Strong foundations in machine learning and statistics, with demonstrable production experience.</li><li>
Practical experience with LLMs and generative AI &mdash; prompting, RAG, fine-tuning, and evaluation.</li><li>
Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.</li><li>
Proficiency in Python and the modern data / ML stack; sound data engineering instincts.</li><li>
Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).</li><li>
Experience supporting business development or pre-sales.</li><li>
Domain depth in a regulated or data-rich industry.</li><li>
Contributions to open source, publications, or a visible professional profile.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will lead substantive, end-to-end AI work in a practice that is scaling fast and backing its people to grow with it. You will shape how a team works, influence how clients adopt AI, and keep your own skills at the frontier, bridging proven data science with the most current GenAI and agentic techniques. It is an opportunity to lead, deliver, and keep building.</div>

Lead Data Scientist (Classical ML, LLMs & AI Agents)

NTT DATA

<div>We&rsquo;re a business with a global reach that empowers local teams, and we undertake hugely exciting work that is genuinely changing the world. Our advanced portfolio of consulting, applications, business process, cloud, and infrastructure services will allow you to achieve great things by working with brilliant colleagues, and clients, on exciting projects.
Our inclusive work environment prioritises mutual respect, accountability, and continuous learning for all our people. This approach fosters collaboration, well-being, growth, and agility, leading to a more diverse, innovative, and competitive organisation. We are also proud to share that we have a range of Inclusion Networks such as: the Women&rsquo;s Business Network, Cultural and Ethnicity Network, LGBTQ+ &amp; Allies Network, Neurodiversity Network and the Parent Network.
For more information on Diversity, Equity and Inclusion please click here: Creating Inclusion Together at NTT DATA UK | NTT DATA
Primary Responsibilities:
<ul><li>Client Engagement &amp; Delivery
</li><li>Data Pipeline Development (Batch and Streaming)
</li><li>Snowflake &amp; Cloud Data Platforms
</li><li>Data Architecture &amp; Modelling
</li><li>Collaboration &amp; Best Practices
</li><li>Quality, Governance &amp; Security 
</li></ul>Business Relationships:
<ul><li>Solution Architects
</li><li>Data Engineers, Developers, ML Engineers and Analysts
</li><li>Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics leadership
</li></ul>Competencies / Critical Skills: 

<ul><li>Proven experience in data engineering and pipeline development on Snowflake and cloud-native platforms.
</li><li>Strong consulting values with ability to collaborate effectively in client-facing environments.
</li><li>Hands-on expertise across the data lifecycle: ingestion, transformation, modelling, governance, and consumption.
</li><li>Strong problem-solving, analytical, and communication skills.
</li><li>Experience leading or mentoring teams of engineers to deliver high-quality scalable data solutions. 
</li></ul>Technical Expertise:
<ul><li>Deep expertise with Snowflake features (warehouses, Snowpark, data sharing, performance tuning).
</li><li>Proficiency in ETL/ELT tools such as DBT, Matillion, Talend, or equivalent.
</li><li>Strong SQL and Python (or equivalent language) skills for data manipulation and automation.
</li><li>Hands-on experience with cloud platforms (AWS, Azure, GCP).
</li><li>Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).
</li><li>Familiarity with data lake architectures and distributed processing frameworks (e.g., Spark, Hadoop).
</li><li>Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.
</li><li>Understanding of data governance, security, and compliance frameworks.
</li><li>Exposure to AI/ML workloads desirable. 
</li></ul>Experience, Qualifications, and Education:
<ul><li>Experience: Minimum 5&ndash;8 years in data engineering, data warehousing, or data architecture roles, with at least 3+ years working with Snowflake.
</li><li>Education: University degree required.
</li><li>Preferred: BSc/MSc in Computer Science, Data Engineering, or related field
</li><li>Snowflake certifications (SnowPro Core, Advanced) highly desirable. 
</li></ul>Measures of Success:
<ul><li>Delivery of high-performing, scalable, and secure data pipelines aligned to client requirements.
</li><li>High client satisfaction and successful adoption of Snowflake-based solutions.
</li><li>Demonstrated ability to innovate and improve data engineering practices.
</li><li>Contribution to the growth of the practice through reusable assets, accelerators, and technical leadership.
</li></ul>We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options.
You can find more information about NTT DATA UK &amp; Ireland here: https://uk.nttdata.com/
We are an equal opportunities employer. We believe in the fair treatment of all our employees and commit to promoting equity and diversity in our employment practices. We are also a proud Disability Confident Committed Employer - we are committed to creating a diverse and inclusive workforce. We actively collaborate with individuals who have disabilities and long-term health conditions which have an effect on their ability to do normal daily activities, ensuring that barriers are eliminated when it comes to employment opportunities. In line with our commitment, we guarantee an interview to applicants who declare to us, during the application process, that they have a disability and meet the minimum requirements for the role. If you require any reasonable adjustments during the recruitment process, please let us know. Join us in building a truly diverse and empowered team.
We are seeking an accomplished and detail-oriented Snowflake Data Engineer to join our Data &amp; AI practice. The successful candidate will bring deep expertise in data engineering, ETL/ELT pipelines, and cloud-native data platforms, with a strong focus on Snowflake. This role is critical in building and optimising modern data ecosystems that enable data-driven decision making, advanced analytics, and AI capabilities for our clients. 
 
As a trusted practitioner, you will collaborate with architects, developers, and analysts to design, implement, and maintain secure and high-performing data pipelines. You will thrive in a collaborative, client-facing environment, with a passion for solving complex data challenges, driving innovation, and ensuring the seamless delivery of data solutions.</div>

Snowflake Data Engineer

The AA

<div><h3 class="jobSectionHeader">Company Description/ Business Unit</h3>
Location: London (hybrid working 3 office days per week)

Employment Type: Permanent, full time

Additional Benefits: Annual Bonus

Think the AA is just about roadside assistance? Think again.

For over a century, we've been evolving and adapting. Today, as the nation's leading motoring organisation, we offer a wide range of products and services to millions of customers. From roadside assistance to home and motor insurance, and the latest driving technologies, we have it all. As we continue to expand, diversify, and modernise, joining us as a Data Scientist means you'll play a crucial role in our success and be part of this exciting motoring journey.

Our Chief Operating Office (COO) are the backbone of The AA, providing both stability and structure to support growth and innovation. We are the drivers of change.

#LI-Hybrid<h3 class="jobSectionHeader">
This is the job</h3>
Data is one of the AA&rsquo;s biggest opportunities, and we are investing in the tools, platforms and AI capability to use it better. As a Data Scientist, you will help us turn complex data into practical solutions that improve how we forecast demand, optimise workforce deployment and support better decisions across our roadside operation.

This role is particularly focused on demand and supply forecasting, using machine learning to help ensure the right patrol capability is available in the right place at the right time. You will work on real operational challenges linked to national workforce planning, resource optimisation, customer demand, service levels and operational performance.

We are looking for someone who enjoys solving complex, real-world problems with data. You may have gained experience in organisations with large field-based, mobile or nationally deployed workforces, such as logistics, delivery, utilities, transport, airlines, emergency services, mobility or roadside operations. You will bring strong analytical thinking, practical data science capability and the confidence to translate technical insight into meaningful recommendations that help the business make better operational decisions.<h3 class="jobSectionHeader">
What will I be doing?</h3><ul>
<li>Build and deploy statistical models and machine learning solutions to support forecasting, product development, value driver analysis and operational performance.</li>
<li>Use data mining, modelling and algorithmic approaches, including AI and LLM-enabled techniques where appropriate, to solve complex business problems.</li>
<li>Work with data, engineering, architecture and AI Centre of Excellence colleagues to design and embed scalable algorithms into AA platforms, products and channels.</li>
<li>Analyse trends, evaluate scenarios, assess risks and uncover insight that supports better business and customer outcomes.</li>
<li>Explore, onboard and use relevant data sources, ensuring data is appropriate, reliable and aligned to good data governance practice.</li>
<li>Communicate findings clearly through presentations, workshops and stakeholder conversations, translating technical insight into meaningful business recommendations.</li>
</ul><h3 class="jobSectionHeader">What do I need?</h3>
We are looking for someone who can bring:
<ul>
<li>Experience applying data science, machine learning or advanced analytics to demand forecasting, supply forecasting, workforce planning or operational optimisation.</li>
<li>Strong capability in Python, SQL and statistical modelling, with experience building practical models that support business decision making.</li>
<li>Experience working with complex operational data, ideally linked to mobile workforces, field operations, logistics, transport, delivery, utilities, emergency services, airlines, mobility or roadside operations.</li>
<li>The ability to turn ambiguous operational challenges into clear analytical questions, scalable models and actionable recommendations.</li>
<li>Strong communication skills, with the confidence to explain complex analysis clearly to technical and non-technical stakeholders.</li>
<li>An understanding of responsible data use, data quality and governance, with exposure to Databricks, Git, Jira, ML Ops, feature stores or data pipelines being beneficial.</li>
</ul><h3 class="jobSectionHeader">Additional information</h3>
We&rsquo;re always looking to recognise and reward our employees for the work they do. As a valued member of The AA team, you&rsquo;ll have access to a range of benefits including:
<ul>
<li>25 days annual leave plus bank holidays + holiday buying scheme</li>
<li>Worksave pension scheme with up to 7% employer contribution</li>
<li>Free AA breakdown membership from Day 1 plus 50% discount for family and friends</li>
<li>Discounts on AA products including car and home insurance</li>
<li>Employee discount scheme that gives you access to a car salary sacrifice scheme plus great discounts on healthcare, shopping, holidays and more</li>
<li>Company funded life assurance</li>
<li>Diverse learning and development opportunities to support you to progress in your career</li>
<li>Dedicated Employee Assistance Programme and a 24/7 remote GP service for you and your family</li>
</ul>
Plus, so much more!

We&rsquo;re an equal opportunities employer and welcome applications from everyone. The AA values diversity and the difference this brings to our culture and our customers. We actively seek people from diverse backgrounds to join us and become part of an inclusive company where you can be yourself, be empowered to be your best and feel like you truly belong. We have five communities to bring together people with shared characteristics and backgrounds and drive positive change.

#LI-HH</div>

Data Scientist

PROXIMIE

<div>Proximie is on a mission to improve healthcare by transforming the world&rsquo;s operating rooms into connected ecosystems of people, devices, and data.<div>
Our Intelligence Suite transforms operating room (OR) performance, keeping teams in sync and workflows on track to maximise throughput. Simultaneously our computer vision and AI capabilities capture real-time data and detect surgical events &ndash; improving quality of data outputs. The result: ORs are optimised like never before &ndash; with predictive analytics and automated notifications ensuring patients and staff are in the right place at the right time.
Once practitioners are in the OR, our Surgical Suite enables real-time remote access and creates a secure video record of every procedure; improving training, education, and collaboration. It is an intuitive asset which helps instil a culture of continuous learning, accelerates the adoption of cutting-edge medical devices, and enhances surgical performance across the entire global workforce &ndash; improving outcomes and saving lives.
Proximie was commercialised in 2019 and is available in over 500 facilities globally.
Check out our Founder and CEO Nadine&rsquo;s Origins Story here: https://www.proximie.com/about-us/
Position Overview
As Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drives better insights and decisions making, using your deep technical expertise and real-world experience you will be instrumental in developing and deploying machine learning solutions that improve clinical outcomes, drive productivity and support Proximie&rsquo;s continuing evolution into the unrivalled champion of the intelligent operating room.
You will work with multi-modal data (audio, vision, and language) to curate, consolidate, and augment retrospective and prospective datasets that fuel the development of advanced machine learning solutions. You&rsquo;ll harness the power of Proximie&rsquo;s deep data lakes and apply cutting-edge generative techniques to solve real-world challenges for Proximie&rsquo;s customers. You&rsquo;ll also lead the development of intelligent systems that can automatically detect and capture key events in the operating room, designing robust solutions that work across diverse and unpredictable data distributions, tackling challenges like identifying rare events buried in hours of surgical video.
This role demands creativity, precision, and a deep understanding of real-world machine learning at scale. If you&rsquo;re excited by complex problems with life-changing impact and want to build tech that operates in the most critical environments, we&rsquo;d love to hear from you.
Responsibilities<ul><li>
Collaborate with product, engineering and commercial teams to develop and deploy AI models for real world application in hospitals all over the world.</li><li>
Design, train and validate machine learning mono and multi-modal models using state of the art approaches.</li><li>
Develop models and derived tools robust to the heterogeneity of operating room environments. With customers all over the world operating rooms are often different which creates unique opportunities for problem solving and model design.</li><li>
Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance.</li><li>
Development within Proximie environment to enable dynamic model training and performance evaluation while integrating with Proximie&rsquo;s data lakes.</li><li>
Document solutions and contribute to internal knowledge sharing and capability building.</li></ul><div>
Requirements<ul><li>
PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but PhD preferred.</li><li>
Minimum of 4 years&rsquo; hands-on experience in industry, developing and deploying AI solutions which solve real-world problems.</li><li>
Expertise in developing, training and fine-tuning machine learning and multi-modal models. Experience in training models with data originating from heterogeneous distributions is highly desirable.</li><li>
Deep knowledge of a variety of traditional machine learning, deep learning and generative AI methods for both supervised, self-supervised and unsupervised learning with an emphasis on vision.</li><li>
Proficiency with deep learning frameworks such as TensorFlow/PyTorch.</li><li>
Proficiency with Python and strong software development background.</li><li>
Knowledge and experience with AWS is highly desirable.</li><li>
Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable.</li><li>
Ability to communicate complex technical concepts clearly to non-technical stakeholders.</li></ul>
Why Work for Proximie?<ul><li>
You will be encouraged to grow in your role, take ownership and gain responsibilities. Proximie&rsquo;s values are Ownership, Deliver Results, Build Trust and Go Beyond.</li><li>
Generous annual leave.</li><li>
Two &ldquo;well-being&rdquo; days per year plus the day off for your birthday.</li><li>
&ldquo;Summer Fridays&rdquo; &ndash; early office closing on Fridays during summer months.</li><li>
Annual bonus programme &ndash; based on individual contribution.</li><li>
To support your professional growth, all permanent employees will have access to an annual stipend of &pound;1,000 to assist with personal development activities.</li><li>
Flexible working hours - we trust our people to manage their time and to focus on wider results.</li><li>
A flat organizational structure where every opinion matters, ideas are cultivated, and innovation is encouraged.</li><li>
Proximie is a truly global company with teams across the UK, Europe, United States and the Middle East with that you will have opportunities to see the world.</li></ul>
Proximie is an equal opportunity employer. We are committed to providing a work environment that supports, inspires, and respects all individuals. We do not discriminate on the basis of race, colour, 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 the law.</div></div></div>

Senior Machine Learning Engineer

JPMorganChase

<div>JOB DESCRIPTION 
 
 
<div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>The Chief Data &amp; Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. As a part of CDAO, The Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy Machine Learning Solutions for our most challenging business problems. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.
As an intern within the MLCOE, you will apply sophisticated machine learning methods to a diverse range of complex domains, including natural language processing, large language models, speech recognition and understanding, reinforcement learning, and recommendation systems. You will collaborate closely with MLCOE mentors, business experts, and technologists, conducting independent research and deploying solutions into production. A strong passion for machine learning, solid expertise in deep learning with hands-on implementation experience, and a commitment to continuous learning and innovation are essential. This role offers a unique opportunity to contribute to and learn from a world-class machine learning team. Learn more about our MLCOE team at jpmorgan.com/mlcoe.
Our Summer Associate Internship Program begins in June, depending on your academic calendar. Your professional growth and development will be supported throughout the internship program via project work related to your academic and professional interests, mentorship, an engaging speaker series with our senior leaders and more. Your project will have direct impact on JPMorgan's businesses, will be integrated into our product pipelines, or be part of published research in top AI/ML conferences. Full-time employment offers may be extended upon successful completion of the program within our hybrid work model.
Job responsibilities<ul><li>
Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community</li><li>
Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems</li><li>
Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Enrolled in a PhD or MS in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, Data Science, or related fields, or equivalent research or industry experience,</li><li>
Expected graduation date of December 2026 through August 2027</li><li>
Solid background in NLP, large language models, speech recognition and modelling, or personalization/recommendation. Familiarity with state-of-the-art practice in these domains</li><li>
Proficient in Python, and experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)</li><li>
Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals</li><li>
Solid written and spoken communication to effectively communicate technical concepts and results to both technical, and business audiences</li><li>
Ability to work both independently and in highly collaborative team environments</li></ul>
Preferred qualifications, capabilities, and skills<ul><li>
Strong background in Mathematics and Statistics</li><li>
Familiarity with the financial services industries</li><li>
Published research in areas of natural language processing, deep learning, or reinforcement learning at a major conference or journal</li><li>
Ability to develop and debug production-quality code</li><li>
Familiarity with continuous integration models and unit test development</li><li>
Published research in areas of natural language processing, speech recognition, reinforcement learning, or deep learning at a major conference or journal</li></ul>
#MLCOE_jobs 
</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.</div></div></div>

2026 Machine Learning Center of Excellence (NLP)-Internship

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As AI moves from experimentation to enterprise-wide adoption, doing it responsibly has become a commercial necessity, not just an ethical one. We are looking for a Responsible AI Specialist to ensure the solutions we design and the advice we give to clients are trustworthy, compliant, and fair by design. This is a role for someone who can translate principles (fairness, transparency, accountability) into practical frameworks that engineering teams and clients can actually apply.
You will be a connective figure across the practice: advising delivery teams on ethical and regulatory risk, contributing to client governance conversations, and helping shape the standards by which we build. You do not need to be a deep technical engineer, but you must understand how AI systems work, where they fail, and what good governance looks like in practice, particularly as regulation such as the EU AI Act reshapes expectations.
This is a growing area of strategic importance, offering significant scope to define our approach and to become a recognised voice in responsible AI.
Required skills &amp; experience:<ul><li>
Define and implement Responsible AI frameworks, policies, and practical guidelines across the practice.</li><li>
Advise project teams on ethical AI design, risk identification, and mitigation throughout the delivery lifecycle.</li><li>
Conduct AI risk and impact assessments, and embed fairness, transparency, and accountability into solutions.</li><li>
Contribute to client conversations on AI governance, risk, and regulatory readiness.</li><li>
Monitor evolving regulation (EU AI Act, ICO guidance, emerging standards) and translate it into actionable guidance.</li><li>
Support internal capability building, raising awareness and competence in responsible AI across teams.</li><li>
Partner with architects and data scientists to operationalise governance &mdash; model documentation, evaluation, and guardrails.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 3 years in AI ethics, governance, policy, risk, compliance, or a closely related regulatory field.</li><li>
Sound understanding of AI concepts, risks, and failure modes (deep technical implementation not required).</li><li>
Working knowledge of relevant regulation and standards, including the EU AI Act.</li><li>
Strong stakeholder communication skills, able to engage both technical teams and senior business audiences.</li><li>
Ability to turn principles into pragmatic, usable frameworks and processes.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting or advisory roles.</li><li>
Familiarity with assurance frameworks (ISO/IEC 42001, NIST AI RMF).</li><li>
Background in data protection, privacy, or model risk management.</li><li>
Exposure to fairness, bias, and explainability tooling.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
Responsible AI is central to how we earn client trust and differentiate our practice. You will have the rare chance to shape this capability from an influential position, combining ethics, regulation, and real delivery in work that genuinely matters. As adoption and scrutiny grow, so will your impact and your profile.</div>

Responsible AI Specialist (Governance, Ethics & Compliance)

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