senior software engineer analytics

Bloomberg

<div>
 Location
 
 
 London
 
 
 Business Area
 
 
 Engineering and CTO
 
 
 Ref #
 
 
 10049302
 
 
 
 Description &amp; Requirements
 
 
 
 Bloomberg&rsquo;s Engineering AI department has 400+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products. At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
 
 
 Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions.
 
 
 Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
 
 
 We are looking for Senior ML Platform Engineers with strong expertise and passion for building platforms for (Gen) AI applications.
 
 
 As a Senior ML Platform Engineer, you will have the opportunity to create a more cohesive, integrated, and managed AI development life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as, Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of open source.
 
 
 
 Join the AI Group as a Senior ML Platform Engineer and you will have the opportunity to:
 
 
 
 <ul>
 <li>
 Architect, build, and diagnose multi-tenant AI platform systems
 </li>
 <li>
 Work closely with AI application teams to design seamless workflows for continuous model training, inference, and monitoring
 </li>
 <li>
 Work with AI experts to understand workflows, pinpoint, and resolve inefficiencies, and to inform the next set of features for the platforms
 </li>
 <li>
 Collaborate with open-source communities and AI application teams to build a cohesive MLOps experience
 </li>
 <li>
 Design CI/CD automation frameworks that incorporate regulatory requirements
 </li>
 <li>
 Develop cloud-native deployment patterns for AI systems across environments
 </li>
 <li>
 Troubleshoot and debug user issues
 </li>
 <li>
 Provide operational and user-facing documentation
 
 
 </li>
 </ul>
 
 We are looking for a Senior ML Platform Engineer with:
 
 
 
 <ul>
 <li>
 Proven years of experience working with an object-oriented programming language (Python, Go, etc.)
 </li>
 <li>
 Experience designing cloud-native, distributed platforms
 </li>
 <li>
 Strong knowledge of Kubernetes, Argo, and container orchestration technologies
 </li>
 <li>
 Previous experience with modern CI/CD tools and GitOps workflows
 </li>
 <li>
 Familiarity with implementing automation for model development lifecycles
 </li>
 <li>
 A proactive mentality and ability to collaborate with peers, stakeholders, and management
 </li>
 <li>
 A Degree in Computer Science, Engineering, Mathematics, or similar field of study or equivalent work experience
 </li>
 <li>
 An understanding of Computer Science fundamentals such as data structures and algorithms
 
 
 </li>
 </ul>
 We give back to the technology community and you can read more about our outreach at:
 
 
 If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role.
 
 
 Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.
</div>

Senior ML Platform Engineer - Artificial Intelligence

Simply Business

<div>
 
 Who Are We?
 
 
 
 We insure small businesses and enable big dreams &ndash; not just for our customers, but for our people and communities too. With over 1,000,000 active insurance policies, we protect builders, bakers, landlords and more than 1,200 other trades.
 
 
 We&rsquo;re a technology company as well as one that sells insurance. That means we build, we fail, we learn and we improve. Through our global social impact strategy, called 'The Big Dreams Project&rsquo;, we're working to help 10,000 small businesses start or grow by 2030.
 
 
 Why not check out our advert on YouTube: Simply Business TV advert 2024: 'Simply the Best'.
 
 
 
 Job Category
 
 
 
 Technology
 
 
 
 Position Type
 
 
 
 Permanent
 
 
 
 Target Openings
 
 
 
 1
 
 
 
 What Is the Opportunity?
 
 
 
 
 Here's What You'll Be Doing
 
 
 
 Data and Analytics (DNA) is the heartbeat of Simply Business, empowering every decision we make with precision and insight. As our Senior Analytics Engineer, you&rsquo;ll be at the forefront of this mission, moving beyond standard reporting to build the high-performance, event-driven data models that power our AI and ML future.This role is a unique blend of technical mastery and strategic influence. You won't just be building pipelines; you&rsquo;ll be pioneering AI readiness by designing low-latency architectures that drive real-time decisions&mdash;from dynamic pricing to risk assessment&mdash;across our entire global operation
 
 
 
 As One Of Our Senior Analytics Engineers, You'll
 
 
 
 <ul>
 <li>
 Design and build authoritative data models in our warehouse, ensuring every asset is robust, scalable, and fully AI/ML ready.
 </li>
 <li>
 Integrate diverse new data sources to enrich our analytical capabilities and provide the complex datasets required for advanced machine learning.
 </li>
 <li>
 Collaborate across engineering and product teams to ensure application designs support sophisticated reporting and real-time AI features.
 </li>
 <li>
 Manage and optimise ELT pipelines that serve as the single source of truth for our Finance, Operations, and Marketing teams.
 </li>
 <li>
 Champion technical standards by mentoring junior engineers and driving best practices in data governance and quality assurance.
 </li>
 <li>
 Pioneer feature engineering pipelines that allow us to challenge the status quo and deliver refreshing, data-led solutions to our customers.
 
 
 </li>
 </ul>
 
 We're Looking For Someone Who Is
 
 
 
 <ul>
 <li>
 A seasoned data expert with 3+ years of experience in analytics or data engineering, specifically modeling and transforming data using tools like dbt.
 </li>
 <li>
 Technically proficient in cloud environments, with hands-on experience using Snowflake or Databricks to manage large-scale data assets.
 </li>
 <li>
 Experienced in building ML features, with a passion for creating the infrastructure that makes artificial intelligence possible.
 </li>
 <li>
 Adaptable and curious, ideally bringing familiarity with various programming languages and an interest in evaluating new tools to drive AI adoption.
 </li>
 <li>
 A proactive problem solver who might have experience with real-time streaming (like Apache Flink) or a background in the insurance domain.
 </li>
 <li>
 A relatable communicator who can translate complex technical architecture into plain English for stakeholders across the business.
 
 
 </li>
 </ul>
 We know it's tough, but please try to avoid the confidence gap. You don't have to match all the bullet points above to be considered for this role.
 
 
 We encourage people of all different backgrounds and identities to apply. We are committed to maintaining an inclusive, supportive place for you to be you and do your very best work.
 
 
 
 Ready to build the future of insurance?
 
 
 
 If you&rsquo;re a tech-minded engineer who thrives on complexity and wants to see your code drive real-world impact, we want to hear from you. At Simply Business, we&rsquo;ve moved past legacy constraints&mdash;we&rsquo;re building a high-scale, event-driven ecosystem where your work on AI-ready data models will directly protect over 900,000 customers. Join a team where your expertise is celebrated, your development is prioritised, and your technical vision helps us redefine what&rsquo;s possible in Insurtech.
 
 
 
 Apply now to start your journey with SB
 
 
 
 
 What Are The Benefits Of Working At Simply Business
 
 
 
 <ul>
 <li>
 we offer a great work-life balance where workloads are manageable and everyone has the flexibility to work hybrid
 </li>
 <li>
 on top of the 25 days annual leave (plus bank holidays), we offer the option to buy five more days of holiday with your flexible benefits
 </li>
 <li>
 our flexible parental leave allows you to approach an important time how you want - with six months full pay to the primary caregiver and four weeks full pay if you're the secondary caregiver
 </li>
 <li>
 our life event leave is an extra days leave every two years for those big moments in your life like moving house or your birthday. And our long-serving employees get a two week paid sabbatical after five years of service, then four weeks off after ten years of service
 </li>
 <li>
 private medical insurance through BUPA, that covers any pre-existing condition is a core benefit. Plus a health cash plan that covers your everyday medical expenses
 </li>
 <li>
 we offer a competitive salary based on your experience and the current market. Plus the potential to earn an annual bonus based on performance
 </li>
 <li>
 access to tools to support your personal development on our dedicated learning platform. As well as support for your mental health with access to counselling
 </li>
 <li>
 we match what you put into your pension up to five per cent. And pass on a tax-free sum that's four times your basic salary with our life assurance policy, with the option to increase it to ten times through our flexible benefit scheme
 </li>
 <li>
 our salary sacrifice car scheme gives you the option to buy a brand new, fully insured, and maintained car for a convenient fixed monthly amount taken from your gross salary (after 6 months service)
 </li>
 <li>
 our flexible benefits scheme gives you an allocated amount to use each year on benefits like critical illness cover, dental insurance, travel insurance, or a gym membership
 
 
 </li>
 </ul>
 Ready to join us and drive our success as a high-performing team? Apply today.
 
 
 
 Employment Practices
 
 
 
 Simply Business is committed to providing equality and opportunities for all employees and candidates considering a career with us. We offer a workplace where colleagues are treated with respect and dignity. We don&rsquo;t (and won&rsquo;t) discriminate either directly or indirectly on the grounds of race, colour, religion, belief, political opinion, disability, nationality, ethnic origin, sex, sexual orientation or relationship status at any stage of the hiring process or during the course of your employment.
</div>

Senior Analytics Engineer

<div>
 
 
 About CRU:
 
 
 
 CRU International is a leading provider of business intelligence and consulting services in the metals, mining, and fertilizer industries. With over 50 years of experience, we offer valuable insights and analysis that help our clients make informed decisions in an ever-changing global market.
 
 
 
 
 
 
 About the role:
 
 
 
 CRU Group is seeking a technically strong, hands-on Senior Data Scientist to join a global team focused on building real-world data science and AI solutions for Risk &amp; Trading workflows. This role will span predictive modelling, machine learning, and modern AI systems powered by large language models.
 
 
 This is an opportunity to own projects end-to-end, from problem framing through to production delivery, working closely with stakeholders, engineers, and technology teams to deliver scalable, product-grade solutions.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Build and deliver solutions across predictive analytics, machine learning, and LLM-based AI.
 </li>
 <li>
 Design, develop, and implement bespoke ML and AI agents and multi-step workflows using modern frameworks such as LangChain, LangGraph, or similar technologies.
 </li>
 <li>
 Develop robust, scalable, production-grade Python code.
 </li>
 <li>
 Partner with senior stakeholders to translate business needs into clear technical requirements and measurable outcomes.
 </li>
 <li>
 Own delivery end-to-end, including problem framing, data discovery, model development, evaluation, integration, deployment, monitoring, and iteration.
 </li>
 <li>
 Collaborate with global teams of analysts, product managers, product modellers, and engineers to deliver high-quality, reliable solutions.
 </li>
 <li>
 Mentor team members and contribute to raising standards for technical execution and delivery discipline.
 </li>
 <li>
 Stay current with developments in machine learning, statistical learning, generative AI, LLMs, and agentic workflows, and identify practical opportunities to apply these technologies within risk and trading services.
 </li>
 </ul>
 
 
 
 
 
 Qualifications:
 
 
 <ul>
 <li>
 MSc or higher in a quantitative discipline such as econometrics, statistics, mathematics, physics, or similar.
 </li>
 <li>
 Expert-level Python skills and strong command of the core scientific stack, including Pandas, Scikit-learn, SciPy, and NumPy.
 </li>
 </ul>
 
 
 
 
 
 Skills &amp; Experience:
 
 
 <ul>
 <li>
 3&ndash;5+ years of experience in data science, machine learning, econometrics, or a related technical field.
 </li>
 <li>
 Proven track record of independently delivering solutions, including model design, training, evaluation, deployment, and monitoring.
 </li>
 <li>
 Strong exposure to time-series forecasting or commodity data.
 </li>
 <li>
 Creative thinker with a robust approach to data and modelling.
 </li>
 <li>
 Hands-on experience working with machine learning and LLMs.
 </li>
 <li>
 Hands-on experience building AI applications beyond simple chatbot interfaces.
 </li>
 <li>
 Goal-oriented, with a high level of energy and enthusiasm; able to operate efficiently, effectively, and professionally in a fast-paced, dynamic, results-driven business environment.
 </li>
 <li>
 Analytical mindset with the ability to quickly understand the intricacies and complexities of commodity data.
 </li>
 <li>
 Creative application of first principles to problems, with an awareness of business time constraints.
 </li>
 <li>
 Approachable, positive, and collaborative, with a genuine interest in developing the team to be the best in the industry.
 </li>
 <li>
 Lead by example in work ethic and commitment to exceeding client expectations.
 </li>
 <li>
 Strong commitment to sharing knowledge and ideas in a constructive and supportive way, with the ability to mentor more junior talent.
 </li>
 <li>
 Delivery-focused, with a passion for quality and innovation, and a flexible, adaptable attitude willing to accept and drive change.
 </li>
 <li>
 Familiarity with Snowflake, AWS, and GCP, or equivalent cloud infrastructure.
 </li>
 <li>
 Strong understanding of modern machine learning workflows and production deployment considerations, including orchestration tools.
 </li>
 </ul>
 
 
 
 
 
 What We Offer:
 
 
 <ul>
 <li>
 Competitive salary and flexible benefits package.
 </li>
 <li>
 Opportunities for professional growth and development as part of a global company.
 </li>
 <li>
 A collaborative and supportive work environment.
 </li>
 <li>
 The chance to work with industry-leading experts and over a diverse range of topics and projects
 </li>
 </ul>
</div>

Senior Data Scientist - GenAI & ML

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 
About the role:
Wise moves billions across borders every year. Behind every transaction is a decision: is this safe? Our ML systems make that call - at scale, in real time, across every market we operate in.
Our Risk ML team is building the next generation of financial crime detection at Wise - investing in modern architectures like deep learning, graph neural networks, and foundation models to detect increasingly sophisticated fraud and money laundering patterns. We're looking for a Staff Applied ML Engineer to lead this evolution: defining the architecture strategy, shipping production neural models, and building the blueprint that scales across FinCrime domains.
This is a greenfield opportunity - you'll be setting the direction for how Wise applies modern ML to financial crime risk, with strong investment and engagement from senior leadership.
How we work:
Risk ML sits within Wise's FinCrime organisation, owning the full ML and AI foundation for financial crime detection. We're scaling into three dedicated pillars - Feature Platform, Learning Loop and Risk Modelling. You'll sit in Risk Modelling, working alongside data scientists, platform engineers, product and domain experts.
We operate with high autonomy and low hierarchy. You'll own problems end-to-end - from research and architecture decisions through to production deployment and impact measurement. We value engineers who shape direction, not just execute tickets.
What will you be working on?<ul><li>
Designing and shipping ML and deep learning models for financial crime detection - sequence-based, graph-based, attention-based - serving real-time decisions at Wise's scale</li><li>
Defining the architecture strategy for how Wise applies modern ML to risk - which model families, which serving patterns, which training paradigms</li><li>
Building the reusable end-to-end pipeline pattern - from experimentation through training to production deployment - that future models follow</li><li>
Evaluating and prototyping foundation model and embedding approaches for transaction representation across FinCrime domains</li><li>
Partnering with Data Science on model evaluation, experimentation design and causal measurement in domains where clean A/B testing isn't always possible</li><li>
Mentoring engineers and data scientists on modern ML fundamentals, production best practices, and architectural decision-making</li></ul>
What do you need?<ul><li>
Production experience shipping deep learning models at scale - systems serving real traffic under latency constraints</li><li>
Ability to make architecture-level decisions independently - model selection, training infrastructure, serving strategy - and explain the reasoning and tradeoffs</li><li>
Experience designing ML systems with hard latency and throughput requirements, including optimisation decisions (quantization, pre-computed embeddings, batching strategies)</li><li>
Strong fundamentals in deep learning: gradient dynamics, attention mechanisms, graph message-passing, sequence modelling</li><li>
Track record of influencing technical strategy across teams - you don't just build, you shape direction</li><li>
Python, PyTorch (or equivalent), distributed training, ML pipeline orchestration</li></ul>
Nice to Have:<ul><li>
Experience in FinCrime, fraud detection, AML, or regulated financial services</li><li>
Experience with graph-based methods (GNNs, entity resolution, link analysis) in production</li><li>
Foundation model fine-tuning or LLM evaluation experience</li><li>
Experience establishing modern ML practices in organisations scaling their ML capabilities</li></ul>
Interested? Find out more:<ul><li>
How we work &ndash; a practical guide</li><li>
DEI @ Wise</li><li>
Wise Tech Stack (2025 update)</li><li>
See what it's like to work at Wise London!</li><li>
Our Engineering career map</li><li>
Wise Engineering &ndash; https://medium.com/wise-engineering</li></ul>
What do we offer:<ul><li>
Starting salary: &pound;145,000 - &pound;182,000 + RSUs</li><li>
Wise Benefits</li></ul>
#LI-AB3 #LI-Hybrid 
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>

Staff Applied ML Engineer - Financial Crime

HOMETRACK

<div>Hybrid working pattern - 2 days per week from London Bridge Office
Hometrack is seeking an experienced Senior Data Engineer to join our product team to help us deliver Hometrack's Data Services ambitions. By building the best property data sets available, which back the market leading AVM, trusted by 17 out of the top 20 mortgage lenders in the UK, we open the door to helping all our customers make the decisions that matter to them - to buy, to lend, to build.
The Data Services team works with 100s of customers across the property sector ranging from mortgage lenders, house builders, investors, fin &amp; proptech, insurers, telco, retail and utilities, as well as others involved in the housing market. Our mission is to inform decision makers by putting the UK&rsquo;s most trusted property data and insights at the heart of the property ecosystem.
Our market intelligence and customer acquisition, retention and engagement solutions are relied upon by leading industry professionals.
Data Services has a diverse product range covering market, property and mover intelligence, delivered through varying mechanisms including data platforms, reports and APIs, providing maximum flexibility when matching our customers&rsquo; needs to the most effective data solution.
Hometrack is looking for an experienced senior data engineer to help us make this a reality.
What we&rsquo;re looking for in a Senior Data Engineer:<ul><li>
Be accountable for team outcomes, playing your part in achieving team goals and ensuring your contribution positively impacts overall success</li><li>
Be a continual improver, looking for ways to help the team do better and be better, again and again</li><li>
Write maintainable, testable code and enjoy providing code reviews</li><li>
Be experienced with Databricks, Delta Lake and Lakehouse architecture for efficient data management; experience with ETL processes and optimizing data pipelines for performance</li><li>
Be strong in Python, SQL, and PySpark</li><li>
Be passionate about building data products for stakeholders and customers, ensuring they are stable, scalable, secure, accurate, observable, and performant</li><li>
Enjoy collaborating closely with colleagues in Product, Analytics, Security, and Software, explaining technical concepts to non-technical audiences</li></ul></div>

Senior Data Engineer

Cushman & Wakefield

<div>Job Title
Junior Analytics Engineer
Job Description Summary
Job Description
As a Junior Analytics Engineer within the EMEA Business Intelligence team, you will be an integral part of the Analytics Engineering pillar, contributing to the development and maintenance of the data foundation that powers BI delivery across EMEA. Working closely with senior Analytics Engineers, you will support the design and build of semantic models, curated datasets, and reusable data assets on our central data platform, gaining hands-on experience with enterprise-scale data modelling and platform engineering in a collaborative, high-performing team. You will work in close collaboration with the BI and Data Science &amp; Engineering teams, helping to lay the groundwork for data assets that increasingly support AI and agentic use cases alongside traditional BI delivery. You will start to develop an understanding of the business context behind the data you work with, helping to translate business needs into well-structured data assets and beginning to build the analytics translation skills that connect data and business outcomes. This is a role for someone who is technically curious, eager to learn, and motivated to build a strong foundation in analytics engineering. You will be guided and supported throughout, with clear opportunities to grow your skills, take on increasing responsibility, and develop toward a more senior role within the pillar.
Responsibilities:<ul><li>
Contribute to the design, build, and maintenance of semantic models and curated datasets on our central data platform, working under the guidance of senior Analytics Engineers.</li><li>
Support the standardisation of datasets, business logic, and data models to enable reusability and consistency across BI teams and markets.</li><li>
Assist with onboarding market-specific datasets onto our central data platform, collaborating with local stakeholders to understand data sources and requirements.</li><li>
Work closely with senior team members to ensure data assets meet the requirements of BI products being developed by the BI Development team.</li><li>
Develop a working understanding of the business context behind data requests, supporting senior team members in translating business needs into data structures and logic.</li><li>
Collaborate closely with Data Science &amp; Engineering colleagues, building familiarity with how data assets are used and shared across teams.</li><li>
Contribute to data quality checks and basic performance monitoring of data models and semantic layers, supporting senior team members in identifying improvements.</li><li>
Support early-stage work on building data foundations that can be used for AI and agentic use cases, such as preparing clean, well-structured datasets ready for future AI applications.</li><li>
Maintain clear documentation of data models, datasets, and platform assets, ensuring work is well-described and easy for others to understand and build on.</li><li>
Participate in peer reviews of data models and platform assets, incorporating feedback constructively to develop technical skills and maintain quality standards.</li><li>
Follow established best practices for data modelling, naming conventions, and platform governance, developing familiarity with the team's standards and ways of working.</li><li>
Engage actively in training, bootcamps, and mentoring programmes, taking ownership of personal development and building expertise in the tools and technologies used by the team.</li><li>
Support testing and quality assurance activities across project delivery, helping to ensure data assets and platform changes are reliable before release.</li></ul>
Requirements:<ul><li>
Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Statistics, or a related technical discipline.</li><li>
Some practical experience with data engineering, analytics engineering, or BI development through employment, internships, or academic projects.</li><li>
Foundational understanding of SQL and a willingness to develop proficiency in building and optimising data models.</li><li>
Basic familiarity with data modelling concepts such as star schema or dimensional modelling; formal experience is an advantage but not required.</li><li>
Exposure to enterprise data platforms such as Databricks, Microsoft Fabric, Azure Synapse, or Snowflake is desirable.</li><li>
Awareness of Power BI or other BI tools and an interest in understanding how data assets underpin BI product development.</li><li>
Curiosity about AI, machine learning, and agentic technologies, and how data platforms are structured to support these use cases.</li><li>
An interest in understanding business needs and translating them into data and analytics solutions, with a willingness to develop commercial awareness alongside technical skills.</li><li>
Strong attention to detail and a methodical approach to building, testing, and documenting data assets.</li><li>
A collaborative and proactive mindset, with the eagerness to learn from senior team members and contribute to a high-performing team.</li><li>
Good communication skills, with the ability to ask clear questions and document work clearly.</li><li>
Knowledge of the real estate sector is a plus but not required.</li><li>
Fluent in English; additional European languages are an advantage.</li></ul> 
Cushman &amp; Wakefield is an equal opportunity / affirmative action employer. All qualified candidates will receive consideration for employment without regard to ethnicity, gender, gender identity or expression, sexual orientation, age, disability, religion, marital status, or any other legally protected characteristic. Cushman &amp; Wakefield is committed to equity in employment, and our goal is to have a diverse, inclusive and barrier-free workplace. If you are a person with a disability and need any other accessible accommodations during the hiring process, you are invited to bring this to the Talent Acquisition Advisor&rsquo;s attention once they have made contact. 

INCO: &ldquo;Cushman &amp; Wakefield&rdquo;</div>

Junior Analytics Engineer

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 
As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.
This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,
You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.
Required skills &amp; experience:<ul><li>
Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.</li><li>
Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.</li><li>
Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.</li><li>
Translate solution designs into clean, well-documented, production-minded code.</li><li>
Contribute to model evaluation, testing, and monitoring.</li><li>
Support and guide very junior and graduate resources, reviewing their work and helping them grow.</li><li>
Help peers unblock technical problems and share knowledge across the team.</li><li>
Take part in client and team discussions and communicate your work clearly.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Typically, 2&ndash;4 years' experience in data science, machine learning, or AI engineering.</li><li>
Solid grounding in core data science and machine learning.</li><li>
Practical experience with LLMs and generative AI, including prompting and RAG.</li><li>
Familiarity with how AI agents are built and orchestrated.</li><li>
Strong Python and common data/ML libraries; good engineering habits.</li><li>
Clear communicator and collaborative team player.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Exposure to cloud AI platforms, Azure a plus.</li><li>
Experience practicing MLOps and LLMOps.</li><li>
Early experience mentoring junior colleagues.</li><li>
Interest in consulting and client-facing delivery.</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:
This is a role built for momentum, working across the full spectrum of modern AI, learning from senior architects and leads on real engagements, with genuine responsibility from day one and a clear path into a leadership track.</div>

AI Engineer (LLMs, Agents & Applied Data Science)

Explore 337+ Senior software engineer analytics in London this July. Find roles across top companies and apply now to boost your career.