lead data scientist

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)

Wise

<div>Company Description 
Wise is a global technology company, building the best way to move and manage the world&rsquo;s money. 
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money. 
For everyone, everywhere.
More about our mission and what we offer. 
Job Description 
We are seeking a talented quantitative developer to join our Treasury Markets Data Science team. This role focuses on owning and operating the production infrastructure behind our FX pricing, risk, and trading systems with the opportunity to broaden the scope of work into traditional quant aspects.
Your work will have a direct impact on Wise&rsquo;s mission and millions of our customers. 
About the Role:
You'll join the Treasury Markets Data Science team, owning the quantitative infrastructure that powers how Wise manages FX risk across a USD 250bn+ in annual FX volume- serving everyone from retail customers sending money abroad to tier-1 banks via Wise Platform.
The wider Treasury FX team includes quants, traders, analysts, product managers and engineers working together to price, hedge, manage and scale FX operations within Wise in real time. Within that, the Data Science team owns the quantitative platform:
We run a Python-first, production-grade quant platform: real-time curve construction, multi-instrument pricing, risk analytics, and trading strategy - all built and operated by the same team. Your primary focus is keeping these systems reliable, performant and well-engineered - while thinking deeply about how they serve customers and products. You'll also contribute to the quantitative models themselves as you grow into the domain.
What you&rsquo;ll own<ul><li>
Python microservices that run quantitative models in production</li><li>
Monitoring, alerting, and reliability for real-time pricing and risk systems</li><li>
Shared quant libraries used across multiple services</li><li>
CI/CD pipelines, deployment and operational excellence</li><li>
Incident response and root cause analysis for production issues</li></ul>
Where you&rsquo;ll grow<ul><li>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</li><li>
Pricing models for new instruments and products</li><li>
Trading strategy development and optimisation</li><li>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</li><li>
Backtesting frameworks and model validation</li><li>
Customer behaviour modelling, pricing strategy and product launch support</li><li>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</li></ul> 
Qualifications 
What we&rsquo;re looking for<ul><li>
4+ years building and maintaining production Python systems</li><li>
Strong experience with microservices, databases, and production infrastructure</li><li>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</li><li>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</li><li>
Experience with testing, monitoring, and debugging complex systems under load</li><li>
A product mindset - you think about who uses your systems and why</li><li>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</li></ul>
It&rsquo;s a bonus if you are familiar with<ul><li>
FX or financial markets experience</li><li>
Term structure modelling, stochastic calculus or Monte Carlo methods</li><li>
Interest rate curve bootstrapping</li><li>
Algorithmic execution experience</li><li>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</li></ul>
We&rsquo;re people without borders &mdash; without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you&rsquo;re passionate about learning new things and keen to join our mission, you&rsquo;ll fit right in.
Also, qualifications aren&rsquo;t that important to us. If you&rsquo;ve got great experience, and you&rsquo;re great at articulating your thinking, we&rsquo;d like to hear from you.
And because we believe that diverse teams build better products, we&rsquo;d especially love to hear from you if you&rsquo;re from an under-represented demographic 
Additional Information<div></div> 
For everyone, everywhere. We're people building money without borders &mdash; without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences. 
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on LinkedIn and Instagram.</div>

Lead Data Scientist (Quant) - Treasury FX

Wise Australia Investments

<div><div><div>Wise is a global technology company, building the best way to move and manage the world&rsquo;s money. 
Min fees. Max ease. Full speed.
Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money.
As part of our team, you will be helping us create an entirely new network for the world's money. 
For everyone, everywhere.
. 
Job Description 
We are seeking a talented quantitative developer to join our Treasury Markets Data Science team. This role focuses on owning and operating the production infrastructure behind our FX pricing, risk, and trading systems with the opportunity to broaden the scope of work into traditional quant aspects.
Your work will have a direct impact on Wise&rsquo;s mission and millions of our customers. 
About the Role:
You'll join the Treasury Markets Data Science team, owning the quantitative infrastructure that powers how Wise manages FX risk across a USD 250bn+ in annual FX volume- serving everyone from retail customers sending money abroad to tier-1 banks via Wise Platform.
The wider Treasury FX team includes quants, traders, analysts, product managers and engineers working together to price, hedge, manage and scale FX operations within Wise in real time. Within that, the Data Science team owns the quantitative platform:
We run a Python-first, production-grade quant platform: real-time curve construction, multi-instrument pricing, risk analytics, and trading strategy - all built and operated by the same team. Your primary focus is keeping these systems reliable, performant and well-engineered - while thinking deeply about how they serve customers and products. You'll also contribute to the quantitative models themselves as you grow into the domain.
What you&rsquo;ll own<ul><li>
Python microservices that run quantitative models in production</li><li>
Monitoring, alerting, and reliability for real-time pricing and risk systems</li><li>
Shared quant libraries used across multiple services</li><li>
CI/CD pipelines, deployment and operational excellence</li><li>
Incident response and root cause analysis for production issues</li></ul>
Where you&rsquo;ll grow<ul><li>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</li><li>
Pricing models for new instruments and products</li><li>
Trading strategy development and optimisation</li><li>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</li><li>
Backtesting frameworks and model validation</li><li>
Customer behaviour modelling, pricing strategy and product launch support</li><li>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</li></ul> 
Qualifications 
What we&rsquo;re looking for<ul><li>
4+ years building and maintaining production Python systems</li><li>
Strong experience with microservices, databases, and production infrastructure</li><li>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</li><li>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</li><li>
Experience with testing, monitoring, and debugging complex systems under load</li><li>
A product mindset - you think about who uses your systems and why</li><li>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</li></ul>
It&rsquo;s a bonus if you are familiar with<ul><li>
FX or financial markets experience</li><li>
Term structure modelling, stochastic calculus or Monte Carlo methods</li><li>
Interest rate curve bootstrapping</li><li>
Algorithmic execution experience</li><li>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</li></ul>
We&rsquo;re people without borders &mdash; without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you&rsquo;re passionate about learning new things and keen to join our mission, you&rsquo;ll fit right in.
Also, qualifications aren&rsquo;t that important to us. If you&rsquo;ve got great experience, and you&rsquo;re great at articulating your thinking, we&rsquo;d like to hear from you.
And because we believe that diverse teams build better products, we&rsquo;d especially love to hear from you if you&rsquo;re from an under-represented demographic 
Additional Information<div></div> 
For everyone, everywhere. We're people building money without borders &mdash; without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive.
We're proud to have a truly international team, and we celebrate our differences. 
Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
Keep up to date with life at Wise by following us on </div></div><div><div><div><div>Instagram</div></div></div></div></div><div></div>

Faculty

<div><h2 class="jobSectionHeader">Why Faculty? 
</h2> 
We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we&rsquo;ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.
We don&rsquo;t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.
Our business, and reputation, is growing fast and we&rsquo;re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.
AI is an epoch-defining technology, join a company where you&rsquo;ll be empowered to envision its most powerful applications, and to make them happen.<h2 class="jobSectionHeader">
About the team</h2>
Our Retail and Consumer experts are dedicated to helping clients in an industry which is being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive.
#LI-PRIO<h2 class="jobSectionHeader">
About the role</h2>
As a Principal Data Scientist, you'll serve as a recognised authority and strategic force across the organisation, shaping not just how we deliver but how we evolve. You will define our technical vision at the highest level, influence organisation-wide strategy, and take ultimate ownership of our most critical, complex, and commercially significant programmes. This position goes beyond project delivery &mdash; you are a multiplier of capability, a trusted partner to senior leadership, and a key driver of long-term competitive differentiation.<h2 class="jobSectionHeader">
What you'll be doing:</h2><ul><li>
Defining and owning the long-term technical vision for the practice, setting standards that raise the bar across the entire organisation.</li><li>
Architecting and overseeing the delivery of flagship, business-critical programmes &mdash; spanning multiple workstreams, teams, and client organisations.</li><li>
Driving organisation-wide adoption of innovation, tooling, and best practices &mdash; influencing how the entire Data Science craft evolves.</li><li>
Cultivating senior talent across the organisation &mdash; coaching leads and managers, building capability pipelines, and embedding a culture of technical excellence.</li><li>
Acting as the senior technical voice in C-suite and executive client engagements, shaping strategic direction and securing long-term partnerships.</li><li>
Leading on the most strategically significant sales opportunities, providing technical authority that differentiates our proposition and wins high-value engagements.</li><li>
Partnering with Engineering, Commercial, and Infrastructure leadership to align technical strategy with broader business goals and growth ambitions.</li></ul><h2 class="jobSectionHeader">
Who we're looking for:</h2><ul><li>
You are a recognised expert in multiple machine learning domains, with the technical breadth to make sound judgements across the full data science landscape.</li><li>
You have a proven track record of shaping technical strategy at an organisational level &mdash; not just within projects, but across business units and leadership forums.</li><li>
You have led the delivery of large-scale, high-ambiguity programmes and can bring clarity, structure, and momentum to the most complex situations.</li><li>
You are a skilled developer of senior people &mdash; coaching leads and managers, building capability, and shaping a high-performance culture.</li><li>
You operate naturally at the executive level &mdash; with clients and internal stakeholders alike &mdash; as a trusted advisor who can translate technical thinking into commercial outcomes.</li><li>
You have a visible external profile &mdash; through publications, conference contributions, open-source leadership, or industry influence &mdash; that reflects your standing in the field.</li><li>
You think beyond the immediate &mdash; identifying emerging opportunities and risks and proactively shaping the organisation's response before they arrive.</li></ul><h2 class="jobSectionHeader">
Our Interview Process</h2><ul><li>
Talent Team Screen (30 minutes)</li><li>
Introduction to the team (30 minutes)</li><li>
Take Home Technical Assessment</li><li>
Technical Interview (90 minutes)</li><li>
Commercial Interview (60 minutes)</li></ul><h2 class="jobSectionHeader">
Our Recruitment Ethos</h2>
We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We&rsquo;re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.
Some of our standout benefits:<ul><li>
Unlimited Annual Leave Policy</li><li>
Private healthcare and dental</li><li>
Enhanced parental leave</li><li>
Family-Friendly Flexibility &amp; Flexible working</li><li>
Sanctus Coaching</li><li>
Hybrid Working</li></ul>
If you don&rsquo;t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.</div>

Principal Data Scientist

DEFRA

Head of Responsible AI and Assurance

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact. 
 
Key job responsibilities 
<ul><li>Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale</li><li>Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning</li></ul>
- Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges 
<ul><li>Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale</li><li>Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact</li><li>Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability</li><li>Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements</li></ul> 
About the team 
What is Amazon Strategic Account Services (SAS)? 
The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.
</div><h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>PhD, or a Master's degree and experience in building models for business application</li><li>Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact</li></ul> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Applied Scientist II, Strategic Account Services (SAS)

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Applied Scientist II, Strategic Account Services (SAS)