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

Lloyds Banking Group

<div>End Date
Wednesday 29 July 2026
Salary Range
&pound;92,701 - &pound;109,060
We support flexible working &ndash; click here for more information on flexible working options
Flexible Working Options
Hybrid Working, Job Share
Job Description Summary
.
Job Description
<div><div>JOB TITLE: Lead Data Scientist
</div><div>SALARY: &pound;92,701 - &pound;109,060
</div><div>LOCATION: Edinburgh, Leeds, Manchester &amp; Bristol
</div><div>HOURS: Full time (35 hours)
</div><div>WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at one of our office sites. Colleagues with disabilities can be supported with workplace adjustments including hybrid working expectations in line with our Flexibility Works policy. 
</div><div>About this opportunity&hellip;
</div><div>At Lloyds Banking Group, we&rsquo;re moving to the next stages of our digital transformation, and it&rsquo;s our job within the Chief Security Office (CSO) to ensure that we keep our customers, colleagues and assets safe from threat. The CSO&rsquo;s Security Data and AI lab have a phenomenal opportunity for an experienced and dynamic Lead Data Scientist to work with our Analytics and Data Engineering feature teams. 
</div><div>In this role, you&rsquo;ll be owning the way in transforming how we detect, mitigate, and prevent cyber threats using advanced AI and machine learning. This is a rare opportunity to build the future of cybersecurity in one of the UK&rsquo;s most data-rich environments. 
</div><div>About us&hellip;
</div><div>Like the modern Britain we serve, we&rsquo;re evolving. Investing billions in our people, data and tech to transform the way we meet the ever-changing needs of our 26 million customers. We&rsquo;re growing with purpose. Join us on our journey and you will too&hellip; 
</div><div>What you&rsquo;ll do...
</div><div><ul><li>Own the delivery of security outcomes , including d efin ing and evolv ing approaches to anomaly detection that balanc e performance, explainability, and operational risk .
</li></ul></div><div><ul><li>Lead a team of Data Scientists
</li></ul></div><div><ul><li>Drive innovation in LLM-based security automation, including prompt engineering, RAG pipelines, and fine-tuning of models.
</li></ul></div><div><ul><li>Collaborate with Data Engineers to build scalable, secure, and production-ready ML pipelines on GCP.
</li></ul></div><div><ul><li>Partner with cyber defence, risk, and compliance teams to ensure models are explainable, ethical, and aligned with regulatory standards (e.g. SOC2, SWIFT, SOX).
</li></ul></div></div><div><div><ul><li>C ontribute to the Data Science Community of Practice, helping shape best practices across the organisation.
</li></ul></div><div><ul><li>Translate sophisticated data insights into actionable intelligence for collaborators across the Group COO and CSO functions 
</li></ul></div><div>What you&rsquo;ll need...
</div><div><ul><li>Confirmed experience in leading data science projects in cybersecurity, fraud, or behavioural analytics.
</li></ul></div><div><ul><li>Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch ), and cloud platforms (preferably GCP).
</li></ul></div><div><ul><li>Deep Learning Theory &amp; Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures.
</li></ul></div><div><ul><li>Experience with LLMs and generative AI in production environments is highly desirable.
</li></ul></div><div><ul><li>Artificial Intelligence Ethics - A passion for ethical AI, model governance, and secure ML operations.
</li></ul></div><div><ul><li>Excellent communication and customer engagement skills
</li></ul></div><div><ul><li>Innovators Mentality - An innovator and change agent who keeps up to date with the latest trends and developments in data engineering and cyber security to ensure our strategies remain at the forefront of the industry. 
</li></ul></div><div>It would be great if you also had&hellip;
</div><div><ul><li>Understanding of the emerging threats within Cyber Security 
</li></ul></div><div>About working for us
</div><div>Our focus is to ensure we're inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We want our people to feel that they belong and can be their best, regardless of background, identity or culture. We were one of the first major organisations to set goals on diversity in senior roles, create a menopause health package, and a dedicated Working with Cancer initiative. And it&rsquo;s why we especially welcome applications from under-represented groups. We&rsquo;re disability confident. So, if you&rsquo;d like reasonable adjustments to be made to our recruitment processes, just let us know. 
</div><div>We also offer a wide-ranging benefits package, which includes&hellip;
</div><div><ul><li>A generous pension contribution of up to 15%
</li></ul></div><div><ul><li>An annual bonus award, subject to Group performance
</li></ul></div></div><div><div><ul><li>Share schemes including free shares
</li></ul></div><div><ul><li>Benefits you can adapt to your lifestyle, such as discounted shopping
</li></ul></div><div><ul><li>30 days&rsquo; holiday, with bank holidays on top
</li></ul></div><div><ul><li>A range of wellbeing initiatives and generous parental leave policies 
</li></ul></div><div>If you&rsquo;re excited by the thought of becoming part of our team, get in touch. We&rsquo;d love to hear from you!
</div></div>At Lloyds Banking Group, we're driven by a clear purpose; to help Britain prosper. Across the Group, our colleagues are focused on making a difference to customers, businesses and communities. With us you'll have a key role to play in shaping the financial services of the future, whilst the scale and reach of our Group means you'll have many opportunities to learn, grow and develop.
We keep your data safe. So, we'll only ever ask you to provide confidential or sensitive information once you have formally been invited along to an interview or accepted a verbal offer to join us which is when we run our background checks. We'll always explain what we need and why, with any request coming from a trusted Lloyds Banking Group person.
We're focused on creating a values-led culture and are committed to building a workforce which reflects the diversity of the customers and communities we serve. Together we&rsquo;re building a truly inclusive workplace where all of our colleagues have the opportunity to make a real difference.</div>

Brego

<div>Brego is an automotive technology company using AI and data analytics to help dealerships, lenders, and other industry partners make better vehicle valuation, pricing, and risk decisions. Working at the intersection of software, data, and decision-making, the team focuses on turning complex information into practical products that support smarter outcomes across the automotive market.
As a Lead Data Scientist, you will take ownership of the AI (custom neural networks rather than third-party LLM technology) and machine learning capabilities behind products that influence high-value pricing and risk decisions. This is a hands-on technical leadership role where you will be responsible for designing, building, deploying, and continuously improving production machine learning systems from end to end. You will own the full lifecycle of models, from feature engineering and training through deployment, monitoring, retraining, and ongoing optimisation, working independently while collaborating closely with engineering and product teams to deliver measurable business impact.
Responsibilities<ul><li>
Own the end-to-end lifecycle of production machine learning models, from problem definition through deployment and ongoing optimisation.</li><li>
Design, build and deploy artificial neural network and machine learning models for vehicle valuation, pricing and other analytics.</li><li>
Take responsibility for production model performance, reliability and long-term maintenance.</li><li>
Evaluate model performance and improve predictive accuracy across production models.</li><li>
Develop and maintain automated retraining pipelines to keep models effective over time.</li><li>
Monitor deployed models, investigate issues and implement improvements to ensure models remain accurate and reliable.</li><li>
Design and run experiments, track results and use data to drive model improvements.</li><li>
Work closely with engineering and product teams to integrate models into production systems and deliver business value.</li></ul> 

Requirements 
Must have:<ul><li>
5+ years of experience building and deploying machine learning models in production environments.</li><li>
Strong experience developing and training neural networks for real-world applications.</li><li>
Strong experience with the Python data science ecosystem, including pandas, NumPy and scikit-learn.</li><li>
Hands-on experience with PyTorch or TensorFlow.</li><li>
Strong understanding of machine learning, statistics, and model evaluation methodologies.</li><li>
Experience taking machine learning models from concept through deployment and ongoing production ownership.</li><li>
Experience evaluating model performance, improving predictive accuracy, and maintaining retraining pipelines, model monitoring, and experiment tracking.</li><li>
Experience with feature engineering and working with large, real-world datasets.</li><li>
Experience writing clean, maintainable, production-quality Python code.</li><li>
Experience with SQL for data analysis and data manipulation.</li><li>
Experience deploying ML workloads in cloud environments.</li><li>
Ability to independently own technical projects and make sound engineering decisions with minimal supervision.</li><li>
Strong problem-solving skills with the ability to investigate complex data and modelling challenges.</li><li>
Strong communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders.</li><li>
Experience collaborating with software engineers, product managers, and data engineers.</li><li>
Eligible to work in the UK.</li></ul>
Nice to have:<ul><li>
Experience in the automotive industry or with vehicle data.</li><li>
Experience in pricing, forecasting, risk modelling, or other predictive analytics domains.</li><li>
Experience with MLOps tooling and infrastructure.</li><li>
Experience building automated data and model pipelines.</li><li>
Experience mentoring or providing technical leadership to other data scientists or engineers.</li></ul> 

Benefits 
<ul><li>
Competitive salary of &pound;90,000 - &pound;110,000 per year, depending on experience.</li><li>
Private healthcare.</li><li>
Pension scheme.</li><li>
Fully remote role with flexible working hours.</li><li>
Working from home allowance.</li><li>
Choice of Apple MacBook Pro or high-spec Windows workstation.</li><li>
Learning and progression opportunities.</li><li>
Optional access to our Silverstone office. The team usually meets there around one day per week, but attendance is entirely optional.</li><li>
High levels of ownership and autonomy with the opportunity to shape the company&rsquo;s AI strategy.</li><li>
Collaborative, low-bureaucracy engineering culture that values autonomy, integrity and innovation.</li><li>
Regular company social events.</li><li>
25 days annual leave plus 3 additional days between Christmas and New Year.</li></ul></div>

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>

Royal Schiphol Group

<div>
 
 Nice to know (you)
 
 
 
 <ul>
 <li>
 Met jouw leiderschap zorg je dat IT &amp; Data producten elke dag impactvol, betrouwbaar, veilig en toekomstgericht functioneren binnen de luchthavenoperatie.
 </li>
 <li>
 Je krijgt energie van het combineren van inhoud, people management en stakeholderafstemming.
 </li>
 <li>
 We gaan ervoor: Schiphol moet tot de top-3 van de Europese luchthavens behoren.
 
 
 
 </li>
 </ul>
 
 Connecting your world
 
 
 
 Als Data Scientist Infra help je Schiphol om digitale producten en diensten voorspelbaar, schaalbaar en toekomstvast te maken.
 
 
 Hoe jij dit realiseert? Dat is aan jou. We vertrouwen op de manier waarop jij richting geeft, prioriteiten stelt en people en inhoud bij elkaar brengt. Jij zet jouw talenten in bij:
 
 
 <ul>
 <li>
 Clean &amp; Tidy data team (eerste maanden): je draagt bij aan het kost-kwaliteitsoptimalisatie-initiatief voor schoonmaak op de luchthaven, met directe impact op operationele prestaties en passagierstevredenheid.
 </li>
 <li>
 het groeien van AI binnen het Infrastructure domein, waar AI relevant is. Infrastructure is een domein waar grote ambities liggen voor de komende 10 jaar met veel potentie voor AI. Je draagt bij aan de strategische roadmap vanuit AI, en aan het ontwikkelen van een team van data scientists en machine learning engineers dat hoge kwaliteit AI en ML oplossingen maakt.
 </li>
 <li>
 van POC naar schaalbaar product: je brengt overzicht in lopende AI-initiatieven, bepaalt vervolgstappen en begeleidt de transitie van veelbelovende POC&rsquo;s naar robuuste, production-ready oplossingen die duurzaam waarde leveren.
 </li>
 <li>
 het afstemmen van standaarden en best practices samen met het Data &amp; AI center of excellence, zorgen voor doorvertaling en implementatie binnen het domein.
 </li>
 <li>
 het nemen van eigenaarschap op standaarden en best practices, onder andere via code reviews, kennisdeling en continue verbeterprocessen. Je bent de AI vertegenwoordiger binnen Infrastructure van de Lead Data Scientist (van Data &amp; AI).
 </li>
 <li>
 het cre&euml;ren en behouden van overzicht op de lopende initiatieven en roadmaps.
 </li>
 <li>
 het kwantificeren en challengen van waarde voor portfoliomanagement met PO&rsquo;s, het BPIP leiderschapsteam en stakeholders (je snapt dat &lsquo;goed&rsquo; goed genoeg is).
 </li>
 <li>
 het cre&euml;ren van een positieve, lerende cultuur, het promoten van samenwerking.
 </li>
 <li>
 hands-on ontwikkeling en ondersteuning van de teams.
 
 
 
 </li>
 </ul>
 
 You've got this
 
 
 
 Schiphol verbindt jouw wereld. Met de beste mensen maken we reizen veilig en verantwoord. Jij draagt hieraan bij met jouw unieke talenten, zoals het verbinden van mensen en het sturen op resultaat. Sowieso heb je voor deze functie:
 
 
 <ul>
 <li>
 wo-werk- en denkniveau, bij voorkeur in data science, econometrie, engineering, informatica, statistiek of vergelijkbaar.
 </li>
 <li>
 ten minste 5 jaar ervaring met het bouwen van AI oplossingen in Python (bijv. met scikit-learn, MLflow, Streamlit, PySpark) en het deployen en onderhouden van modellen in een productieomgeving.
 </li>
 <li>
 ervaring met Databricks, cloud computing, containerized application development.
 </li>
 <li>
 goede communicatieve vaardigheden in het Nederlands en Engels, het kunnen uitleggen van technische concepten aan niet-technisch publiek.
 </li>
 <li>
 empathie, verbindend vermogen tot samenwerking, flexibiliteit, eigenaarschap.
 
 
 
 </li>
 </ul>
 
 You get this
 
 
 
 <ul>
 <li>
 &euro; 5703 tot &euro; 7912 bruto per maand (schaal 13).
 </li>
 <li>
 Een NS-Business Card die reizen met openbaar vervoer van en naar het werk helemaal vergoedt.
 </li>
 <li>
 180 vakantieuren.
 
 
 
 </li>
 </ul>
 Dit zijn nog maar een aantal van onze arbeidsvoorwaarden die horen bij deze functie (op basis van een 36-urige werkweek). Schiphol heeft jou nog meer te bieden. Ga voor het totale overzicht van alle arbeidsvoorwaarden naar Arbeidsvoorwaarden - Werken bij Schiphol.
 
 
 
 About The Team
 
 
 
 
 About Schiphol Infrastructure | Business Platform Infrastructure en IT Projects
 
 
 
 Bij Schiphol Infrastructure bedenken, bouwen en beheren we alle fysieke en digitale assets van Schiphol. Dat is onze bijdrage aan de ambitie van Schiphol om een kwalitatieve en duurzame luchthaven te zijn. Met ruim 1000 collega&rsquo;s leveren we, samen met onze ketenpartners, de komende jaren meer projecten op en halen we onderhoudsachterstanden in. Zo verbeteren we de arbeidsomstandigheden door de inzet van robots en tilliften, elektrificeren we de assets op airside en vernieuwen en verduurzamen we cruciale delen als de C-pier, bagagekelder en klimaatsystemen. Tegelijk lossen we storingen op en maken we doordachte investeringskeuzes om onze infrastructuur klaar te maken voor de toekomst.
 
 
 Als afdeling binnen Schiphol Infrastructure combineert Business Platform Infrastructure &amp; Projects (BPIP) twee verantwoordelijkheden: Digital &amp; Technology voor Schiphol Infrastructure &eacute;n IT Project Delivery voor heel Schiphol. Met ruim 200 collega&rsquo;s ontwikkelen en beheren we digitale oplossingen voor Infrastructure en leveren Schiphol brede IT projecten (software en fysieke IT assets) voorspelbaar en met hoge kwaliteit.
 
 
 
 Choose your destination
 
 
 
 Wat zijn jouw talenten? Welke dromen heb jij? Wat is jouw verhaal? We zijn benieuwd naar jou en nodigen je graag uit om te solliciteren.
 
 
 <ul>
 <li>
 Heb je vragen over de inhoud van de functie? Schakel met Robbert Roodhart, D&amp;I manager of Sebastiaan Grasdijk, AI Lead.
 </li>
 <li>
 Heb je vragen over het sollicitatieproces? Stel deze aan Yvette Mulder-van Zon, Recruitment Business Partner, via yvette.mulder-van.zon@schiphol.nl of 06-48438257.
 </li>
 <li>
 Een assessment kan deel uitmaken van het proces.
 
 
 
 </li>
 </ul>
 
 About Schiphol Group
 
 
 
 Met 4.200 trotse collega&rsquo;s zetten we een extra stap om Nederland zo goed mogelijk te verbinden met de rest van de wereld. Vernieuwen, veiligheid en samenwerken staan daarbij voorop. Samen geven we meer betekenis aan reizen en leveren een bijdrage aan economie en maatschappij. Al meer dan 100 jaar. In Nederland en daarbuiten. Wist je trouwens dat:
 
 
 &hellip; Schiphol Group eigenaar en exploitant is van Amsterdam Airport Schiphol, Rotterdam The Hague Airport en Lelystad Airport? We hebben ook een meerderheidsbelang in Eindhoven Airport.
 
 
 &hellip; er in 2023 circa 442.000 vliegbewegingen van en naar Schiphol Airport waren?
</div>

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