junior programmer

MarketCast

<div>
 
 Junior Data Scientist - Product
 
 
 
 
 London, UK, Reading, UK
 
 
 
 
 Role Impact
 
 
 
 As our Junior Data Scientist - Product, you'll be a pivotal player on our Data Science Product Team, which currently comprises about 15 data scientists with varying levels of seniority.
 
 
 The Junior Data Scientist - Product plays a foundational role in supporting the design, engineering, execution, and delivery of advanced data science projects and market research products at Marketcast. Operating at the intersection of quantitative market research, software engineering, and artificial intelligence, this position focuses on building the backend systems and data pipelines that clean, process, and analyse complex datasets to extract actionable consumer insights. On a daily basis, the Junior Data
 
 
 Scientist assists in writing production-quality code, developing and maintaining data pipelines, implementing machine learning models, and translating analytics into robust, reusable product features under senior guidance. By ensuring high data quality, engineering rigour, and contributing to innovative product features, this individual directly enhances the reliability and scalability of the organisation's media and entertainment analytics.
 
 
 
 We're Looking For
 
 
 
 <ul>
 <li>
 Data Engineering and Pipeline Development &ndash; Design, build, and maintain reliable data pipelines that clean, preprocess, and structure complex quantitative datasets using Python, SQL, pandas, and modern data tooling. This technical processing is performed systematically and reproducibly, with an emphasis on well- structured, version-controlled, and testable code to prepare raw survey and consumer data for downstream statistical models. Ensuring clean inputs and resilient pipelines directly prevents model drift and maintains the reliability of product outputs. Success in this responsibility is defined by the timely delivery of error-free, analytical-ready, and maintainable data pipelines to senior data scientists.
 </li>
 <li>
 Quantitative Analysis &amp; Modelling - Assist in executing statistical analyses, regression modelling, and audience segmentation under the guidance of senior team members, with a strong emphasis on mathematical rigour and a sound understanding of the methods being applied rather than their black-box use.
 </li>
 <li>
 Backend &amp; Software Development - Contribute to the backend services, APIs, and codebases that power our data products, writing clean, tested, and well-documented code under senior guidance. The analyst works within standard software engineering practices - version control, code review, automated testing, and CI/CD - to ship features that are reliable and maintainable rather than one-off scripts. This software-first approach ensures our analytical work translates into durable product infrastructure. Success is measured by code quality, adherence to engineering standards, and the stability of contributions in production.
 </li>
 <li>
 Infrastructure &amp; Deployment - Support the deployment, monitoring, and scaling of data science workloads across our cloud and infrastructure stack (e.g. containers, orchestration, and managed cloud services) under supervision. The analyst helps operationalise models and pipelines so they run reliably and cost-effectively at scale, contributing to the team's MLOps and engineering practices. This focus on robust infrastructure reduces manual intervention and improves the reliability of our products. Performance is evaluated on the stability, reproducibility, and efficiency of deployed workloads.
 </li>
 <li>
 AI &amp; LLM Integration - Support the integration of artificial intelligence APIs, large language models (LLMs), and natural language processing pipelines into existing data products. Under supervision, the analyst helps configure frameworks to streamline analytical workflows, saving dozens of hours of manual coding on client projects. Performance is evaluated on the efficiency, robustness, and classification accuracy of the automated NLP routines.
 </li>
 <li>
 Data Quality &amp; Validation - Execute rigorous quality control protocols across all assigned data products and research databases, including automated tests and validation checks wherever possible. The Junior Data Scientists systematically validate schemas, sample distributions, and statistical weights to verify data integrity, treating data validation as an engineering discipline. This preventative auditing mitigates the risk of reporting flawed conclusions to high-profile entertainment clients. Successful execution is measured by the complete absence of formatting or calculation errors in final delivery files.
 </li>
 <li>
 Client Collaboration &amp; Technical Delivery &ndash; Work closely with product managers, engineers, and senior data scientists in a collaborative, software-development style &ndash; gather requirements, contributing to technical scoping, and participating in agile ceremonies and code reviews.
 </li>
 <li>
 Cross-Functional Initiative Support - Participate actively in company-wide product development initiatives, research-on-research experiments, and technical thought leadership groups. The Junior Data Scientist collaborates across data operations, cloud engineering, product, and engineering departments to support the trial of new analytical and engineering methodologies. This cross-pollination of ideas ensures the product data science team remains at the forefront of marketing science and technical innovations. Engagement in these initiatives is demonstrated by active participation in internal sharing sessions and support for pilot projects.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 We genuinely don&rsquo;t mind what is written on your certificate. While we would love you to have a formal qualification in any discipline that builds strong analytical and problem-solving skills, we primarily care that you're clever, rigorous, and can do the job. Equivalent practical experience - whether self-taught, through bootcamps, open-source contributions, a strong portfolio, or prior industry work - is just as welcome as a formal degree.
 </li>
 <li>
 A successful applicant must demonstrate solid programming ability (Python and ideally SQL) and an interest in writing good, maintainable software - not just scripts.
 </li>
 <li>
 A successful applicant must further demonstrate a genuine appetite for technical depth, mathematical rigour, and continuous learning.
 
 
 </li>
 </ul>
 
 Who We Are
 
 
 
 MarketCast measures what moves people. Powered by AI, trained on decades of verified consumer response data, and backed by proprietary technology, MarketCast is the marketing effectiveness partner for the world's most ambitious brands, connecting emotional resonance to real-world business outcomes across advertising, sponsorships, content, brand health, and advanced analytics. With category-deep expertise spanning sports, entertainment, travel, automotive, and consumer brands, our team of
 
 
 seasoned industry strategists brings unmatched human intelligence to every engagement, turning complex data into decisive action so brands know exactly what's working, why it's working, and what to do next.
 
 
 At MarketCast, we don't just accept difference - we embrace it, support it, and thrive on it for the benefit of our global culture and success. MarketCast is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know. Check us out on LinkedIn and at: www.marketcast.com
 
 
 
 Our Values
 
 
 
 
 Move The Needle
 
 
 
 We turn insight into action and action into impact, acting with urgency and intention at every level, anticipating what's needed, executing with discipline, and driving outcomes that are measured and meaningful.
 
 
 
 Client Success is Our Scoreboard
 
 
 
 We win when our clients win. Delivering scaled, tech-enabled solutions that drive measurable impact and value to build lasting partnerships.
 
 
 
 Grow Every Day
 
 
 
 Expertise is earned continuously by investing in our craft, our colleagues, and our company.
 
 
 
 Own It
 
 
 
 Take responsibility for outcomes, not just outputs.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Free movie tickets!
 </li>
 <li>
 29 days annual leave PLUS Bank Holidays
 </li>
 <li>
 Flextime with core hours between 10am and 3pm
 </li>
 <li>
 2 days&rsquo; work from home per week
 </li>
 <li>
 4% match pension scheme
 </li>
 <li>
 Enhanced maternity pay
 </li>
 <li>
 Regular social events in both UK locations
 </li>
 <li>
 Professional growth and career development including LinkedIn Learning
 
 
 </li>
 </ul>
 In addition to your salary, MarketCast believes in providing a competitive total rewards package for its employees. All benefits are subject to eligibility requirements, and the terms of our official plan may be modified or amended from time to time.
 
 
 GENERAL DATA PROTECTION REGULATION (UK GDPR) NOTICE: The organisation collects and processes personal data relating to its applicants, employees and former employees to manage pre-employment and employment relationships and post-employment obligations. The organisation is committed to being transparent about how it collects and uses that data and to meeting its data protection obligations. For further information on the information we collect, how it&rsquo;s used, and how it's protected, please contact the MarketCast UK HR Team.
</div>

Junior Data Scientist I

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

VodafoneThree

<div><div><div><div><h2 class="jobSectionHeader">Who we are</h2>
</div><div>
VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology &amp; Transformation.
 
As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next-generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth. With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry-first model which brings together the best of in-house and 3rd party capability.
 
We work with customers across 28 countries from 10 VOIS locations: Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.
 
#VOIS #BeUnrivalled #CreateTheFuture</div></div><div><div><h2 class="jobSectionHeader">
About this Role:</h2>
</div><div>
The Digital &amp; IT Team is responsible for designing, building, and operating the core digital and IT capabilities that power Vodafone&rsquo;s next‑generation Digital &amp; IT platform.
As a Junior AI Engineer, you will work within cross-functional squads to build platform capabilities using an AI-enabled Software Development Life Cycle (AI-SDLC).
You will apply AI tools to accelerate how we understand existing systems, generate specifications, and deliver software, working alongside engineers, architects, and product teams.
You will help transform existing platform assets and business requirements into structured, reusable engineering artefacts, supporting delivery through spec-driven, thin-slice development.
You will also support the responsible use of AI-generated outputs by validating accuracy, completeness, security, and alignment with Vodafone engineering standards.
Given the responsibilities outlined above, the role includes:<ul><li>
Supporting analysis of existing systems to extract business logic, integrations, and reusable capabilities</li><li>
Generating structured engineering artefacts to support consistent delivery</li><li>
Contributing to AI-assisted development workflows, ensuring alignment between requirements, specifications, and implementation</li><li>
Supporting incremental, thin-slice delivery of platform capabilities</li><li>
Working closely with developers, architects, and product teams to maintain quality, consistency, and delivery pace</li></ul></div></div><div><div><h2 class="jobSectionHeader">
What you&rsquo;ll do</h2>
</div><div><ul><li>Use AI tools to support analysis of existing codebases and services, identifying reusable logic and integration patterns</li><li>
Generate and refine specifications, acceptance criteria, and user stories aligned to platform architecture</li><li>
Create test scenarios and validation artefacts derived from specifications</li><li>
Support translation of business requirements into implementation-ready engineering artefacts</li><li>
Work with developers to ensure alignment between specifications, code, and testing outputs</li><li>
Validate AI-generated specifications, code suggestions, test scenarios, and documentation to ensure they are accurate, secure, consistent, and aligned with platform architecture and engineering standards</li><li>
Support responsible AI-SDLC practices by identifying risks such as hallucinated requirements, incomplete logic, security gaps, or misalignment between business intent and implementation</li><li>
Contribute to incremental, thin-slice delivery, maintaining traceability between requirements, specifications, and implementation</li><li>
Assist in the implementation of services, APIs, and platform components, validating AI-generated outputs</li><li>
Participate in agile ceremonies (refinement, planning, stand-ups, retrospectives)</li><li>
Contribute to AI-SDLC practices, templates, and continuous improvement across the squad.</li><li>
AI-Assisted Engineering - Understanding of how AI tools support system analysis, specification, and delivery workflows</li><li>
Software Engineering Fundamentals - Knowledge of APIs, data structures, and system design basics</li><li>
AI Governance and Validation - Awareness of responsible AI usage in software delivery, including validation of AI-generated outputs, traceability, quality control, and security considerations</li><li>
Collaboration - Works effectively in cross-functional squads, supporting engineers and product teams</li><li>
Communication - Able to clearly document specifications and communicate technical concepts</li><li>
Learning Mindset - Strong curiosity and ability to rapidly adopt new tools and practices</li><li>
Agile Delivery - Exposure to iterative delivery, CI/CD, and continuous improvement practices</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Who you are</h2></div><div> 
<ul><li>
Experience with at least one programming language (e.g. Java, Python, JavaScript or similar)</li><li>
Understanding of APIs, web services, and basic system integration concepts</li><li>
Familiarity with modern development workflows (Git, CI/CD basics)</li><li>
Awareness of AI/LLM tools and their application in software development</li><li>
Exposure to cloud-native development concepts (e.g. microservices, containers, or cloud platforms)</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Not a perfect fit?</h2>
</div><div>
Concerned you may not meet every requirement? Vodafone is committed to creating an inclusive workplace where everyone can thrive. If you are excited about this role but your experience does not align exactly with every aspect of the job description, you are encouraged to apply. You may be the right candidate for this or another opportunity, and the recruitment team will support you in exploring where your skills fit best.</div></div><div><div><h2 class="jobSectionHeader">
VOIS Equal Opportunity Employer Commitment</h2>
</div><div>
Vodafone recognises and celebrates the value of diversity in building a workforce that reflects the customers and communities it serves. No form of discrimination is tolerated. This includes, but is not limited to, discrimination based on race, colour, age, veteran status, gender identity, gender expression, sexual orientation, pregnancy, maternity or parental status, ethnicity, disability, religion or belief, political affiliation, trade union membership, nationality, citizenship, indigenous status, medical condition, HIV status, neurodiversity, social origin, cultural background, marital or civil partnership status, or socio-economic background.</div></div><div><div><h2 class="jobSectionHeader">
Join Us</h2>
</div><div>
At Vodafone, we&rsquo;re working hard to build a better future. A more connected, inclusive and sustainable world. As a dynamic global community, it's our human spirit, together with technology, that empowers us to achieve this.
 
We challenge and innovate in order to connect people, businesses, and communities across the world. Delighting our customers and earning their loyalty drive us, and we experiment, learn fast and get it done, together.
 
With us, you can truly be yourself and belong, share inspiration, embrace new opportunities, thrive, and make a real difference.</div></div><div><div><h2 class="jobSectionHeader">
Alert
</h2></div><div>Apply for Vodafone jobs only through the official Vodafone Careers website to avoid job scams and fraud.
 
#JDEnhancedByTARA</div></div></div></div>

Junior AI Software Engineer

Few&Far

<div>
 
 🚨
 
 Senior Data Engineer | Outside IR35 Contract | Up to &pound;525/day | London (1 day onsite)
 
 🚨
 
 
 
 
 
 I'm working with a growing business that's looking for a Senior Data Engineer to join on an initial 6-12 month contract.
 
 
 
 
 
 💰
 
 Up to &pound;525 per day
 
 
 
 📍
 
 London - 1 day per week onsite
 
 
 
 📄
 
 Outside IR35
 
 
 
 ⚡
 
 1-stage interview process
 
 
 
 
 
 
 This is a fantastic opportunity to play a key role in modernising a cloud-based data platform while helping to future-proof the company's infrastructure and mentoring junior engineers as they continue to develop.
 
 
 
 
 
 You'll be working on:
 
 
 ✅ Modernising data lake &amp; data warehouse architecture
 
 
 ✅ Designing, building and optimising ETL/ELT pipelines
 
 
 ✅ Deploying and supporting production ML systems, including forecasting models, LLM-powered and agentic workflows
 
 
 ✅ Enhancing an AWS-native data platform (S3, Redshift, RDS, Athena, SageMaker &amp; Lambda)
 
 
 ✅ Writing high-performance SQL and production-quality Python
 
 
 ✅ Improving platform reliability, monitoring and CI/CD
 
 
 ✅ Collaborating with stakeholders to deliver scalable data solutions
 
 
 ✅ Mentoring junior engineers through code reviews and best practices
 
 
 
 
 
 
 Tech Stack:
 
 
 
 ☁️ AWS
 
 
 🐍 Python
 
 
 🗄️ SQL
 
 
 🔄 Airflow (AWS)
 
 
 📊 Looker (nice to have)
 
 
 
 
 
 I'm keen to speak with Data Engineers who have:
 
 
 ✔️ Strong experience building production-grade data pipelines
 
 
 ✔️ Advanced SQL and Python skills
 
 
 ✔️ Experience deploying and supporting ML models in production
 
 
 ✔️ AWS cloud experience and a solid understanding of DevOps/platform engineering
 
 
 
 
 
 If you're available soon or know someone who could be a great fit, please apply below or share this job post!
 
</div>

Senior Data 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)

<div>As one of the world's largest networks of audit, tax and consulting firms, RSM delivers big ideas and premium service to help middle-market businesses thrive. We are a fast-growing firm with big ambitions - we have a clear goal to become the premium adviser to the middle market, globally. This vision touches everything we do, motivating and inspiring us to become better every day. If you are looking for a firm where you can build a future and make an impact, then RSM is the place for you. 
Make an Impact at RSM UK
At RSM, our consulting team brings together diverse advisory experts to deliver our six core solutions: business transformation, forensic, deal services, restructuring, finance function support, and risk and governance. 
 
Our solutions are designed to address the unique needs, challenges, and opportunities our clients face as they strive to achieve their aspirations and organisational goals. Whether it&rsquo;s supporting global expansion, developing acquisition strategies, facilitating private equity investments, or collaborating with boards to manage risk and governance, our consulting experts work as one cohesive team. We prioritise simplicity, providing data-driven insights, value-added assurance, and high-quality execution to empower our clients in building sustainable, future-fit businesses. 
 
It&rsquo;s an exciting time to join our consulting team, as we embark on ambitious growth plans that promise to create diverse career opportunities. We are committed to enhancing our six solutions, expanding and developing our team of expert consultants, embracing a digital-first approach, strengthening our global presence, and building strong client relationships. 
The Data Engineering &amp; Analytics Associate Director is responsible for establishing and leading the data engineering and analytics capability within the Forensic Technology team. The role combines hands-on technical delivery with team leadership and direct client engagement.
Day-to-day, you will design and build data pipelines, analytical models, and automated forensic testing on Microsoft Fabric and Databricks using Python, PySpark, and SQL.
You will work directly with clients, lawyers, and regulators understanding their problems, proposing data-driven solutions, and delivering through to completion.
You will also be responsible for building the team around you: hiring and mentoring junior staff, setting coding and governance standards, and creating the reusable tools and IP that underpin a scalable, consistent analytics capability. This is a greenfield role therefore, you will contribute to defining how the function operates.
You will make an impact by:
You will help establish the data engineering and analytics function, choosing the patterns, setting the standards, and building the team. You will be responsible for delivering analytics solutions directly to clients from day one.<ul><li>
Designing and building production-grade data pipelines on Microsoft Fabric and Databricks to support forensic investigations, transaction analysis, and red flag testing.</li><li>
Presenting analytical findings directly to clients, lawyers, and regulators as part of live forensic engagements.</li><li>
Setting the technical direction for the team: defining coding standards, peer review processes, data governance practices, and documentation requirements.</li><li>
Leading the strategy to leverage and integrate AI into process and output.</li><li>
Mentoring and developing junior data engineers and analysts, and leading hiring as the team grows.</li><li>
Building reusable forensic analytics tools and templates that make the team faster and more consistent over time.</li><li>
Leading proposals and business development activity for forensic data analytics engagements.</li><li>
Collaborating with analytics professionals across the wider Consulting practice through a community of practice.</li></ul> 
What we are looking for:<ul><li>
Strong experience with Microsoft Fabric or previous Azure Synapse components, Databricks an advantage.</li><li>
Strong Spark, SQL and Python skill.</li><li>
Solid understanding of data pipeline design, data modelling, and data governance.</li><li>
Working experience with Power BI and version control (Git, Azure DevOps or similar).</li><li>
Experience with Alteryx is desirable but not essential.</li><li>
Typically 5+ years in data engineering, analytics, or a closely related role.</li><li>
Experience leading a technical team or workstream, including mentoring junior staff.</li><li>
Ability to work with clients to understand their problems, propose data analytics solutions to address their requirements, and lead the delivery of those solutions from scoping through to completion.</li><li>
Experience in professional services, consulting, or a regulated environment is an advantage particularly in forensic or financial crime specialisms.</li></ul> 
What we can offer you:
We recognise that our people are our most important assets. That&rsquo;s why we offer a flexible reward and benefits package that will help you have fulfilling experience, both in and out of work.<ul><li>
Hybrid working although travel to your local office will be required weekly.</li><li>
27 Days Holiday.</li><li>
Lifestyle, Health, and Wellbeing including financial wellbeing benefits such as financial tools, electric car scheme and access to a virtual GP.</li><li>
Access to a suite of 300+ courses on demand developed by our inhouse Talent Development team.</li></ul> 
Diversity and Inclusion at RSM 
At RSM, we want to create a strong sense of belonging so that people of all identities, backgrounds, and cultures feel they can bring their true self to work. Our clients come from all walks of life. We aim to achieve that same diversity of background, experience and perspective in our own teams, so that we can genuinely understand our client's needs. Diverse teams bring a broader range of ideas and insights to work. That's why we're working together to ensure our firm's principles and processes support a firm culture that embraces difference and strengthens inclusion.</div>

Data Engineering & Analytics Associate Director

Accenture

<div>YOU ARE
As a hands-on Infrastructure Architect, you are an experienced engineer with several years in infrastructure engineering who now takes on more complex, higher-impact work designing and optimizing the AI and machine learning infrastructure that powers real-world applications. Working alongside senior architects and engineers &mdash; and increasingly leading your own workstreams &mdash; you apply proven skills in coding, testing, configuring, deploying, monitoring, and troubleshooting AI systems and the infrastructure they run on. Day to day, you architect and optimize infrastructure components, write and review code and deployment scripts, design and tune cloud and on-premises compute resources such as GPU clusters and distributed training environments, deploy AI systems and models into production, and build and optimize data pipelines that feed AI and ML workflows. You optimize the computational stack for performance, cost, power, and scalability, monitor AI systems and infrastructure health across both InfraOps and MLOps disciplines, perform AI monitoring to track model and system performance, and independently troubleshoot and resolve complex issues across the stack. You also mentor junior engineers, contribute to architectural decisions, and help establish best practices. This is a hands-on, ownership-driven where you apply and deepen your expertise across modern tools and platforms &mdash; including container orchestration, model serving, CI/CD pipelines, InfraOps, MLOps, and AI monitoring &mdash; while making meaningful contributions to infrastructure that enables AI-driven business outcomes.
THE WORK<ul><li>
Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling, setting standards for quality across the team.</li><li>
Architect, configure, and provision compute resources across cloud and on-premises environments, including GPU clusters and distributed training setups, optimizing for performance and utilization.</li><li>
Design and maintain deployment automation and CI/CD pipelines to support reliable, repeatable releases of AI systems, models, and applications.</li><li>
Deploy AI systems, models, and data pipelines into production, defining and improving the processes and best practices others follow.</li><li>
Lead container orchestration and model serving using tools such as Docker, Kubernetes, and model deployment frameworks.</li><li>
Architect and optimize the computational stack for performance, power, cost, and scalability, balancing trade-offs against business goals.</li><li>
Evaluate and select tools, frameworks, and platforms, making recommendations that shape the infrastructure roadmap.</li><li>
Integrate AI models and systems into existing enterprise systems, ensuring interoperability, security, and regulatory compliance.</li><li>
Own AI monitoring and infrastructure health across InfraOps and MLOps, tracking performance, reliability, and utilization, and driving remediation.</li><li>
Independently troubleshoot and resolve complex issues across the computational stack &mdash; hardware, networking, software, and models &mdash; and lead root-cause analysis.</li><li>
Mentor junior engineers and lead code reviews, providing technical direction and supporting their growth.</li><li>
Define and document architecture standards, processes, and procedures, and apply security, cost-efficiency, and scalability best practices across the infrastructure.</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree in Computer Science, Computer Engineering, related Engineering field</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experienced with coding, building, monitoring, troubleshooting applications of AI/ML models; selecting, designing and infrastructure for deploying and running them on premise or on public cloud.</li><li>
Strong understanding of AI and machine learning as a subject.</li><li>
Strong understanding of computing infrastructure a subject, preferred knowledge of AI infrastructure.</li><li>
Proficient in programming languages such as Python, Java, or C++.</li><li>
Experience with data pipeline and workflow management tools (e.g., Apache Airflow, Kubeflow).</li><li>
Strong problem-solving skills and ability to work in a fast-paced environment.</li><li>
Excellent communication and collaboration skills.</li><li>
Experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large scale solutions.</li></ul></div>

AI Infrastructure Architecture Specialist

Explore 33+ Junior programmer in London this July. Find roles across top companies and apply now to boost your career.