data scientist

senior data scientist

ai researcher

data analyst

data scientist ii

quantitative researcher

XTX Markets

<div><p><b>The Firm</b><br>
<br>
XTX Markets is a leading algorithmic trading firm. We build models that forecast prices for more than 53,000 financial instruments across equities, fixed income, currencies, commodities and crypto. Those forecasts are used to trade on exchanges and other venues, and to provide liquidity to clients. The firm trades over $250bn a day across 35 countries, with over 300 people in London, Singapore, New York, Paris, Bristol, Mumbai, Yerevan and Kajaani.</p>
<p>
XTX is a technology business. Trading here is driven by research, large-scale computation and careful engineering. Over the last decade our models have moved from the econometric methods that gave the firm its name, through trees and neural networks, to modern deep learning. We expect that evolution to continue, and we are looking for researchers who can push it.</p>
<p>
The research platform is large by any standard, and particularly unusual in trading: well over 25,000 GPUs and more than 1 exabyte of usable storage, with further compute being built in Finland. The point is simple: good ideas should not be bottlenecked by data, infrastructure or compute.</p><br>
<p><b>
The Team</b><br>
<br>
This role sits in XTX's central Quantitative Research team, the group responsible for the firm's core forecasting research. The team reports directly to XTX's founder and is intentionally flat. There is little ceremony and little hierarchy; researchers are expected to have ideas, test them properly, argue from evidence and get useful work into the system.</p>
<p>
The work is modern ML research, not finance by another name. You do not need to have worked in trading. The best candidates usually have strong research taste, mathematical depth and the ability to make models work in practice. An interest in markets helps, because the domain is full of useful structure, but trading intuition can be built here.</p><br>
<p><b>
The Role</b><br>
<br>
Trading is a hard setting for machine learning in ways that are not always obvious from outside the industry. The data is enormous, messy, non-stationary and produced by other agents. Signals are weak and often short-lived. Evaluation is unforgiving: costs, latency, risk and capacity all matter, and a model that looks good in a backtest may still be useless in the market. The time scales also range from microseconds to weeks, so there is no single right abstraction.</p>
<p>
Your job will be to do original research that improves XTX's forecasting and trading systems. Depending on your background, that may mean:</p>
<ul>
<li>Designing and training deep learning models for large-scale time-series and cross-sectional prediction.</li>
<li>Improving representations, objectives, optimisation, regularisation, uncertainty estimates, evaluation methods or scaling.</li>
<li>Making models more robust under distribution shift and feedback from the market.</li>
<li>Working with engineers and trading technologists to turn research into production systems.</li>
<li>Learning enough market structure to ask better modelling questions.</li>
</ul>
<p>This is not about applying standard methods to tidy datasets. It is a place to do serious ML research on difficult data, with enough compute and infrastructure for ambitious ideas to be tested properly.</p><p><br>
<b>
What We Are Looking For</b></p>
<ul>
<li>Evidence of original technical ability in ML, statistics, mathematics, computer science, physics or another quantitative field. Publications are one route, but not the only one; strong industrial research or major open-source contributions can also be good evidence.</li>
<li>Deep practical understanding of modern deep learning: architectures, objectives, optimisation, scaling, evaluation and failure modes.</li>
<li>Strong mathematical and statistical foundations.</li>
<li>Excellent programming ability and comfort working close to the details of implementation.</li>
<li>Good experimental taste: forming hypotheses, designing clean tests, reading ambiguous results and changing your mind quickly when the evidence changes.</li>
<li>High standards, intellectual honesty and the ability to work in a flat team where ideas are challenged directly.</li>
<li>No finance background is needed; the important thing is being willing to learn the domain.</li></ul><br>
<p><br>
<b>Beneficial Experience</b></p>
<ul>
<li>PhD or equivalent research experience in a relevant technical field.</li>
<li>Experience training large models or building ML systems at meaningful scale.</li>
<li>Work in time-series modelling, online or continual learning, reinforcement learning, causal inference, probabilistic modelling, optimisation, compilers, HPC or low-latency systems.</li>
<li>Experience taking research beyond a prototype.</li><br>
</ul>
<p><b>Benefits</b></p>
<p>
Key benefits include:</p>
<ul>
<li>Onsite gym, sauna and fitness classes.</li>
<li>Extensive medical benefits, including onsite doctor and therapist.</li>
<li>Breakfast and lunch provided daily.</li>
<li>Support for caregivers, including emergency dependent care.</li>
<li>King's Cross office.</li>
<li>25 days paid holiday per year, plus statutory holidays and paid sick days.</li>
<li>Generous pension contributions.</li></ul></div>

Quantitative Researcher - Deep Learning

<div><div><div><div>United Kingdom</div>
</div><div><div>Quantitative Analysis, Sales and trading</div>
</div><div><div>Investment Bank
</div></div><div><p><b>Job Reference #</b></p>
<div>339175BR</div>
</div><div><p><b>City</b></p>
<div>London</div>
</div><div><p><b>Job Type</b></p>
<div>Full Time
</div></div><div><p><b>Your role</b></p>
<ul><li>Participate in the design, development, and implementation of quantitative models and analytics supporting the QIS business</li><li>Play a key role in designing and implementing the next generation of AI-powered systems, partnering closely with Trading, Structuring and Sales from idea generation through production launch</li><li>Deliver high quality quantitative applications, tools, and workflows to support QIS Trading, Structuring and Sales in managing, analyzing, and hedging risk</li><li>Contribute to the transformation of the QIS calculation stack, including migration towards a strategic, cloud based architecture in collaboration with IT and platform teams</li><li>Support internal and external stakeholders, including clients, third party calculation agents, and internal platform teams, ensuring robustness, transparency, and scalability of QIS analytics</li><li>Build and maintain strong working relationships with Trading, Structuring, Sales, Quant, IT, and Risk partners in London and across regions</li></ul>
</div><div><p><b>Your Career Comeback</b></p>
<div>We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.</div>
</div><div><p><b>Your team</b></p>
<div>QIS Quants deliver best in class quantitative solutions for clients and trading functions of UBS&rsquo; Quantitative Investment Strategies (QIS) business, part of Global Markets. As a member of our team, you will play a pivotal role in the design, modelling, and delivery of systematic investment strategies, along with the analytics and tooling that support their full lifecycle from conception to production and client delivery. You will be developing models, applications, and workflows within UBS&rsquo;s proprietary cloud based quantitative analytics platform (ACQA), working closely with Trading, Structuring, Sales, Quant, and IT partners globally. Your work will directly support QIS strategy innovation, risk management, and scalable production, contributing measurable value to clients and internal stakeholders.</div>
</div><div><p><b>Your expertise</b></p>
<div>Required:<br>
<ul><li>Strong professional experience in QIS, systematic trading, quantitative research, structuring, or front office quant roles within Global Markets</li><li>Strong proficiency in Python for developing quantitative models, analytics, and production ready applications</li><li>Solid grounding in financial mathematics, time series analysis, and quantitative modelling techniques</li><li>Experience working with large scale data and analytics pipelines.
</li><li>Strong analytical, problem solving, and architectural design skills, with an ability to operate effectively in a front office environment</li><li>Academic background in Quantitative Finance, Mathematics, Physics, Engineering, Computer Science, or a related STEM discipline</li></ul><br>
Preferred:<br>
<ul><li>Strong knowledge of AI/ML techniques, with experience delivering such models into production environments a plus</li><li>Proficiency in Agentic design (LangChain/LangGraph), implementation, and hallucination management; experience with performance critical or large scale systems is a plus</li><li>Experience with strategic cloud platforms and workflows (e.g. Azure based architectures); exposure to migration or platform transformation initiatives is advantageous</li><li>Strong understanding of the end to end lifecycle of systematic strategies, from research and modelling through production and client delivery</li><li>You&rsquo;re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment &ndash; validating outputs and aligning with policies, risk standards, and ethical use</li></ul></div>
</div><div><p><b>About us</b></p>
<div>UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.<br>
We know that great work is never done alone. That&rsquo;s why we place collaboration at the heart of everything we do. Because together, we&rsquo;re more than ourselves. Want to find out more? Visit ubs.com/careers.</div>
</div><div><p><b>Join us</b></p>
<div>At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We&rsquo;re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That&rsquo;s why collaboration is at the heart of everything we do. Because together, we&rsquo;re more than ourselves.<br>
We&rsquo;re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.</div>
</div><div><p><b>Disclaimer / Policy statements</b></p>
<div>UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.</div></div></div></div><div></div>

Senior Quant AI Developer

Wise Australia Investments

<p></p><div><div><div><p>Wise is a global technology company, building the best way to move and manage the world&rsquo;s money.<br>
<b>Min fees. Max ease. Full speed.</b></p><p>
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.</p><p>
As part of our team, you will be helping us create an entirely new network for the world's money.<br>
<b>For everyone, everywhere.</b></p><p>
.</p><p><b><br>
Job Description</b></p><p><b><br>
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.</b></p><p><b>
Your work will have a direct impact on </b><b>Wise&rsquo;s mission</b><b> and millions of our customers.</b><br>
</p><p><b>About the Role:</b></p><p>
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.</p><p>
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:</p><p>
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.</p><p><b>
What you&rsquo;ll own</b></p><ul><li><p>
Python microservices that run quantitative models in production</p></li><li><p>
Monitoring, alerting, and reliability for real-time pricing and risk systems</p></li><li><p>
Shared quant libraries used across multiple services</p></li><li><p>
CI/CD pipelines, deployment and operational excellence</p></li><li><p>
Incident response and root cause analysis for production issues</p></li></ul><p><b>
Where you&rsquo;ll grow</b></p><ul><li><p>
Real-time curve construction (yield curves, FX forwards, vol surfaces)</p></li><li><p>
Pricing models for new instruments and products</p></li><li><p>
Trading strategy development and optimisation</p></li><li><p>
Risk modelling alongside the Risk team (VaR, stress testing, scenario analysis)</p></li><li><p>
Backtesting frameworks and model validation</p></li><li><p>
Customer behaviour modelling, pricing strategy and product launch support</p></li><li><p>
Collaborating with product teams to translate quantitative insights into customer-facing decisions</p></li></ul><p><b><br>
Qualifications</b></p><p></p><p><b><br>
What we&rsquo;re looking for</b></p><ul><li><p>
4+ years building and maintaining production Python systems</p></li><li><p>
Strong experience with microservices, databases, and production infrastructure</p></li><li><p>
Experience with streaming systems, real-time data pipelines, or event-driven architectures (Kafka, Flink, Redis etc.)</p></li><li><p>
Quantitative background - maths, physics, engineering or finance - you can read a model and reason about correctness</p></li><li><p>
Experience with testing, monitoring, and debugging complex systems under load</p></li><li><p>
A product mindset - you think about who uses your systems and why</p></li><li><p>
Clear communicator who can work cross-functionally with other quants, analysts, traders, product managers and engineers</p></li></ul><p><b>
It&rsquo;s a bonus if you are familiar with</b></p><ul><li><p>
FX or financial markets experience</p></li><li><p>
Term structure modelling, stochastic calculus or Monte Carlo methods</p></li><li><p>
Interest rate curve bootstrapping</p></li><li><p>
Algorithmic execution experience</p></li><li><p>
Data lake or warehouse experience (Snowflake, Iceberg, Spark etc.)</p></li></ul><p><b>
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.</b></p><p><b>
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.</b></p><p><b>
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</b></p><p><b><br>
Additional Information</b></p><div></div><p><br>
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.</p><p>
We're proud to have a truly international team, and we celebrate our differences.<br>
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.</p><p>
If you want to find out more about what it's like to work at Wise visit <b>Wise.Jobs</b>.</p><p>
Keep up to date with life at Wise by following us on </p></div></div><p></p><div><div><div><div><b>Instagram</b></div></div></div></div></div><div></div>

Lead Data Scientist (Quant) - Treasury FX

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<p></p><p>At JPMorganChase, you'll be part of a world-class quantitative modeling group that drives innovation in financial engineering, data analytics, and portfolio management.
</p><p>As a Vice President in the Quantitative Trading &amp; Research team, you'll collaborate with traders, risk managers, and controllers to develop and maintain sophisticated models for fair value measurement across multiple business lines. You should be passionate, curious, and ready to make an impact.</p><p><b>
Job responsibilities</b></p><ul><li>
Develop mathematical models for the valuation of credit derivatives, structured lending facilities, and illiquid collateral</li><li>
Implement methodologies for model calibration and build analytics to manage model risk appetite</li><li>
Leverage machine learning, AI, and data analytics to enhance valuation methodologies and drive innovation</li><li>
Define methodology for pricing adjustments, model limitations, parameter uncertainty, and liquidity reserves</li><li>
Monitor model performance metrics to ensure models behave as expected over time</li><li>
Design and develop software frameworks for analytics delivery to systems and applications</li><li>
Collaborate with front office trading desks, controllers, and model risk teams to safeguard the firm's balance sheet</li></ul><p><b>
Required qualifications, capabilities, and skills</b></p><ul><li>
Demonstrated quantitative and problem-solving skills, including research abilities</li><li>
Strong understanding of advanced mathematics in financial modeling (probability theory, stochastic calculus, statistics)</li><li>
Hands-on experience with data analytics, large data sets, and tools for analysis and visualization</li><li>
Proficiency in code design and programming, primarily Python and C++</li><li>
Practical experience with code performance optimization, debugging, and reverse engineering</li><li>
Excellent verbal and written communication and team skills in a multi-location environment</li><li>
Deep understanding of financial products, their valuations, and associated risks</li></ul><p><b>
Preferred qualifications, capabilities, and skills</b></p><ul><li>
Advanced degree (PhD, MSc or equivalent) in Engineering, Mathematics, Physics, Computer Science, etc.</li><li>
Proven quantitative model development or model validation experience</li><li>
Markets experience and familiarity with trading concepts and terminology</li><li>
Knowledge of options pricing theory, trading algorithms, financial regulations, stochastic processes, partial differential equations, and numerical analysis</li></ul>
<b>ABOUT US</b>
<br>
<br>
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.<br>
<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.<br>
</div></div><br>
<br>
<b>ABOUT THE TEAM</b>
<br>
<br>
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Quantitative Trading & Research - Valuation Models - Vice President

Arenko

<div>
 <p>
  <u>
   Who are we?
  </u>
 </p>
 <p>
  Arenko was founded in 2014 and we are growing rapidly in an emerging sector. We&rsquo;d describe ourselves as fast-paced and inclusive. Our team are self-motivated problem solvers who take a collaborative approach to help the business develop and grow.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <u>
   So what do we do?
  </u>
 </p>
 <p>
  As we move to the high-renewables and low carbon era, electricity storage is transforming the way the energy industry operates. The energy industry is fast becoming a digital and multidisciplinary sector that provides a fundamental service for modern society, but these needs must be delivered in a socially responsible way. Arenko is using new technology to add flexibility to the grid and secure supply in this fast-changing industry, offering a huge variety of opportunities for the future. At Arenko we are strongly committed to our mission of building a sustainable future by enabling a zero-carbon grid worldwide. Energy storage has a crucial role to play in the energy transition, and our technology enables the transformation of energy systems. We have committed a Sustainability Strategy more details of which can be found on our website at
  <u>
   https://arenko.group/sustainability/
  </u>
 </p>
 <p>
  <br/>
 </p>
 <p>
  Sound like something you care about? Please read on&hellip;
 </p>
 <p>
  <br/>
 </p>
 <p>
  <u>
   What&rsquo;s the role?
  </u>
 </p>
 <p>
  As a Data Scientist in the Nimbus Trade Optimiser team at Arenko, you will play a key role in shaping and evolving our algorithmic physical power trading strategies. Nimbus Trade is an algorithmic trading product used by traders and asset owners to automate the trading of grid-scale batteries and flexible assets. This role focuses on the data, optimisation, and strategy logic embedded in a production trading system, directly influencing how assets are traded in live energy markets. You will work at the intersection of data science, optimisation, and energy markets, helping to design the next generation of our optimiser and discover new trading and operational strategies in a rapidly changing energy landscape.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Batteries and flexibility are fundamental to operating electricity grids with high levels of intermittent renewable generation. In this role, you will focus on understanding how our optimiser behaves in real market conditions, identifying opportunities to improve performance, robustness, and value capture. You will explore large and complex datasets produced by energy markets, trading systems, and simulations, and translate insights into improvements to optimiser logic, strategy design, and decision-making frameworks. You will work closely with engineers and traders to ensure data-driven ideas are implemented, tested, and evaluated in real market conditions. Your work will directly support trading outcomes for a market-leading client base operating battery and flexibility assets.
 </p>
 <p>
  <br/>
 </p>
 <p>
  You will:
 </p>
 <ul>
  <li>
   Analyse market, trading, and operational data to identify opportunities to improve trading performance, optimiser behaviour, and value capture.
  </li>
  <li>
   Design, develop, and evaluate machine learning, statistical, and optimisation-based solutions to support trading and operational decision-making.
  </li>
  <li>
   Develop and test new trading and operational strategies using historical analysis, simulation, and experimentation techniques.
  </li>
  <li>
   Contribute to the design and evolution of optimiser objectives, constraints, and decision-making frameworks.
  </li>
  <li>
   Collaborate closely with engineers and traders to translate analytical insights into production-ready improvements.
  </li>
  <li>
   Build tools, analyses, and workflows that improve visibility into optimiser performance and reduce reliance on manual processes.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <u>
   Who are you?
  </u>
 </p>
 <p>
  Here at Arenko, we appreciate every single employee and the values they bring to the company so you might be completely different to what we expected. That being said, here&rsquo;s a few things we&rsquo;d love you to tick the boxes on;
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   You&rsquo;re degree level educated in Computer Science or a related discipline
   <strong>
    or
   </strong>
   you&rsquo;re able to demonstrate equivalent workplace experience.
  </li>
  <li>
   You have 2+ years of relevant experience in data science, quantitative analysis, quantitative research, or a closely related role.
  </li>
  <li>
   You&rsquo;re experienced in writing clean, maintainable, and production-ready Python code.
  </li>
  <li>
   You have experience developing, evaluating, and deploying machine learning models, with an understanding of the strengths and limitations of different approaches.
  </li>
  <li>
   You have solid knowledge of applied statistics, probability, and experimental best practices, with an understanding of common pitfalls and their impact on decision-making.
  </li>
  <li>
   You&rsquo;re familiar with optimisation techniques and their application to real-world decision-making problems.
  </li>
  <li>
   You have experience working on quantitative decision-making systems such as trading, optimisation, forecasting, or automated control systems. Experience in energy markets or battery optimisation is advantageous but not required.
  </li>
  <li>
   You&rsquo;re able to explain analytical approaches and findings clearly to both technical and non-technical audiences.
  </li>
  <li>
   You have strong data visualisation and storytelling skills, able to link analysis back to real-world impact.
  </li>
  <li>
   You&rsquo;re a self-motivated and pragmatic problem solver who enjoys working collaboratively in cross-functional teams.
  </li>
  <li>
   You&rsquo;re focused on automation, reproducibility, and building tools rather than repeating manual analysis.
  </li>
  <li>
   You can demonstrate curiosity and a desire to continuously learn, improve, and deepen their understanding of optimisation, trading, and energy markets.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <u>
   So what&rsquo;s in it for you?
  </u>
 </p>
 <p>
  Hopefully the first thing is you love what we do and want to be part of the mission but let&rsquo;s be honest&hellip;that&rsquo;s probably not why you&rsquo;re getting up to work everyday.
 </p>
 <p>
  <br/>
 </p>
 <p>
  We know that rewarding our employees is the best way to make them feel valued. This is a journey we&rsquo;d love you to take with us and as we grow we look forward to finding more ways to reward and thank you for your commitment to our mission. We currently offer the following benefits with more to come in future;
 </p>
 <p>
  <br/>
 </p>
 <ul>
  <li>
   25 days holidays in addition to public holidays, carry over flex and festive office closure (a pretty decent annual leave allowance even if we do say so ourselves!)
  </li>
  <li>
   A genuine approach to flexible working - the vast majority of our employees spend at least a day or 2 each week in the office but we&rsquo;re open to making this work for everyone, their personal circumstances and their workloads
  </li>
  <li>
   Enhanced parental leave offerings with 6 months of full salary for the primary caregiver and 1 month for the secondary caregiver
  </li>
  <li>
   We provide premium Private Medical Insurance through Freedom Elite on a Medical History Disregarded (MHD) basis. In plain English: we generally cover pre-existing conditions from day one - a perk that puts your wellbeing first.
  </li>
  <li>
   A yearly salary review for all employees
  </li>
  <li>
   We are proud to support the continuous professional growth of our employees by providing a personal annual learning and development budget and fully covering the costs of professional membership fees and subscriptions relevant to your role
  </li>
  <li>
   Access to MindTools on us
  </li>
  <li>
   Bike to Work Scheme (because it wouldn&rsquo;t be very on brand if we didn&rsquo;t encourage you to think about how your travel affects the environment)
  </li>
  <li>
   Octopus EV Scheme (see above!)
  </li>
  <li>
   A commitment to your wellbeing, with access to our Employee Assistance Programme and complimentary eye tests in partnership with Specsavers
  </li>
  <li>
   As part of our DEI efforts, we are currently in partnership with MotherBoard which enable us to be committed to improving the working lives of parents at Arenko
  </li>
  <li>
   Regular opportunities to blow off some steam engage with our team, including quarterly socials, the big Festive Gathering and the Summer Party. We&rsquo;re also working on our wellness initiatives to support your Physical, social, mental and financial wellbeing.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <u>
   Our selection process
  </u>
 </p>
 <ol>
  <li>
   First stage interview with hiring manager
  </li>
  <li>
   Take home technical test
  </li>
  <li>
   Second stage with Senior Data Team
  </li>
  <li>
   Final stage with hiring manager and Head of Trade Products
  </li>
 </ol>
 <p>
  <br/>
 </p>
 <p>
  <u>
   Want to join us?
  </u>
 </p>
 <p>
  Here at Arenko, we want every employee and candidate to feel valued, comfortable, and able to be their own free self at work. Together, we are committed to building a diverse and inclusive culture that encourages, supports, and empowers the authentic voices of all our employees. All qualified applicants will receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or any other aspect that makes you unique.
 </p>
 <p>
  <br/>
 </p>
</div>


Data Scientist

Millennium

<div>
 We are working on different areas where AI/ML can help portfolio managers, researchers, risk managers, and other functions. Some examples are: enabling traders/researchers to consume vast amounts of research and literature by organizing, summarizing information, sometimes in near real-time; doing quantitative modeling to price instruments, modeling demand and supply of commodities and other fundamentals; modeling weather, optimizing algorithmic execution of trades; modeling and building simulations of risk.
 <br/>
 <br/>
 The AI/ML work spans usage of LLMs, deep learning, reinforcement learning and other ML techniques. The work also requires building AI/ML infrastructure for data wrangling, building feature stores, building frameworks for deployments, measurements, re-training, etc.
 <br/>
 <br/>
 We are seeking a AI/ML SWE who has experience with LLMs, deep learning, reinforcement learning as well as an interest and ability to keep up with advancements in AI/ML. The candidate should also be strong in software engineering and be comfortable with AI/ML experimentation and productionization.
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  Key Responsibilities
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   Engage and collaborate with business stakeholders, quants, and other market researchers to deeply understand the problem space.
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   Experiment, iterate, productionize AI/ML solutions.
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   Build supporting data and AI/ML infrastructure and tools.
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  Required Skills And Qualifications
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   Strong knowledge of the latest advancements in AI and machine learning.
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   Strong fundamentals in computer science.
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   Proficiency in Python and at least 1 other language such as Java, C++, C#, etc.
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   Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud).
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   Experience with using LLMs and with techniques such as prompt engineering, PEFT, fine-tuning, etc.
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   Ability to build and evaluate AI models and tools using quantifiable metrics.
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   Excellent problem-solving skills and ability to work independently as well as part of a team.
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   Strong communication skills to effectively collaborate with developers and other stakeholders.
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   Adaptable and willing to work in a start-up-like environment within a major institution.
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  Preferred Qualifications
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   Advanced degree in Computer Science, AI, Machine Learning, or a related field.
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   Experience in developing AI solutions for financial institutions.
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   Knowledge of additional programming languages and frameworks.
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 </ul>
</div>


AI Engineer

American Express

<div><p>Credit and Fraud Risk (CFR) is a global function, responsible for making the right credit and fraud risk decisions that uphold operational excellence, drive growth, and accelerate innovation across American Express. CFR combines technology and infrastructure with new computing techniques to make better risk decisions and provide real-time customer communications and fraud servicing.
</p><p>AI Labs seeks an AI Researcher to contribute to advanced research that will power credit, fraud and marketing decisions. The candidate serves as a thought leader and a problem-solver who can blend business, technical, and industry best practices when it comes to developing the models, and algorithms that power our customers&rsquo; digital experiences. This role sits at the intersection of applied AI research, large-scale AI platforms, and large-scale compute infrastructure. The AI researcher will help define and execute a forward-looking research agenda and help to translate cutting-edge machine learning, and systems innovation into scalable, governed, and business-critical AI capabilities. Role is focused on advanced modelling solutions for structured data (tabular data, sequence of events, timeseries, graph-based structures).
</p><p>The ideal candidate will combine deep hand-on ML research expertise with strong practical knowledge and experience in building scalable infrastructure and data science platforms.
</p><p>Colleagues in AI Labs serve as key members of the Global Decision Science organization within Credit and Fraud Risk at American Express. This critical team is responsible for managing enterprise risks throughout the customer lifecycle, across our consumer and commercial businesses, and across all our global products. We develop industry-first data capabilities, build profitable decision-making frameworks, create machine learning-powered predictive models, and improve customer servicing strategies.
</p><p>Our Global Decision Science teams use industry leading modelling and AI practices to predict customer behaviour. We develop, deploy and validate predictive models and support the use of models in economic logic to enable profitable decisions across credit, fraud, marketing and servicing optimization engines.</p></div>
<br><div><ul><li><p>Ph.D degree in Computer Science, Statistics, Operations Research, Engineering, Mathematics, Economics, Physics, or a related quantitative field or equivalent work experience.
</p></li><li><p>Work experience in applied research lab organisations is a plus.
</p></li><li>Very strong record of applied research impact through platforms, patents, production systems, or enterprise-scale adoption, in addition to traditional publications.
</li><li><p>Expertise with GPU-accelerated ML workloads, high-performance computing, and advanced optimization techniques are essential.
</p></li><li><p>Expert knowledge of machine learning and statistical modeling methods for supervised and unsupervised learning in areas such as transformer and attention-based architectures, deep learning for structured sequential and graph data, multi-task and transfer learning.
</p></li><li><p>Exceptional programming skills in Python, Spark. Additional knowledge of C/C++ and Java is preferred
</p></li><li>Expertise in hybrid-cloud AI/ML infrastructure, including Google Cloud (e.g., Vertex AI, BigQuery, Dataproc) and large-scale distributed computing environments.
</li><li><p>Strong knowledge of databases and related languages/tools such as SQL, NoSQL, Hive, etc.
</p></li><li><p>Exceptional people leadership and managerial skills
</p></li><li><p>Ability to work in a dynamic, cross-functional environment, with a strong attention to detail
</p></li><li><p>Effective communication skills and ability to explain complex data products in simple terms
</p></li><li><p>Strong relationship building and collaborative skills.<br>
</p></li></ul><p><br>
Employment eligibility to work with American Express in UK is required as the company will not pursue visa sponsorship for these positions.</p></div>
<br><div><p>At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
</p><p>As part of Team Amex, you&rsquo;ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.</p></div>
<br><div><p>We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
</p><p></p><ul><li>Competitive base salaries
</li><li>Bonus incentives
</li><li>Support for financial-well-being and retirement
</li><li>Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
</li><li>Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
</li><li>Generous paid parental leave policies (depending on your location)
</li><li>Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
</li><li>Free and confidential counseling support through our Healthy Minds program
</li><li>Career development and training opportunities
</li></ul><div><p>Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.</p></div></div>

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