data engineer

data scientist

senior data engineer

analytics engineer

senior analytics engineer

compliance governance data scientist

Rippling

<div><h2 class="jobSectionHeader">About Rippling</h2>
Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system. 
Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365&mdash;all within 90 seconds. 
Based in San Francisco, CA, Rippling has raised $1.4B+ from the world&rsquo;s top investors&mdash;including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock&mdash;and was named one of America's best startup employers by Forbes. 
We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses. 
About the role
We are looking for a Compliance Governance Data Scientist to join our Compliance Risk Office (CRO). As Rippling expands rapidly into regulated markets globally (UK, EU, AU, SG, NZ), our compliance surface is outgrowing our legacy infrastructure. This role is a critical technical hire tasked with closing that gap. 
Moving beyond traditional Financial Crime/AML, you will build the technical data infrastructure to track cross-domain compliance risks across Complaints, Regulatory, Product Governance, and Employer of Record (EOR). You will own the automated aggregation of risk data, stand up our central Management Information (MI) reporting framework, and help launch our proprietary Compliance Risk App. 
The ideal candidate has 2&ndash;3 years of experience writing SQL, building dashboards, and translating qualitative compliance frameworks into quantitative data models. 
What you will do<ul><li>
Transition the CRO from manual data assembly to automated, real-time dashboards that provide a single consolidated view of risk for the Compliance Committee and Board.</li><li>
Serve as the functional data owner for the rollout of our Compliance Risk App, ensuring it serves as the single source of truth for all cross-domain risks.</li><li>
Work closely with our Governance Lead to translate the new compliance risk taxonomy into measurable Key Risk Indicators (KRIs) across all business units.</li><li>
Connect data pipelines from our Monitoring &amp; Testing (M&amp;T) domain programs directly to the central risk register so testing becomes completely risk-based.</li><li>
Run historical and predictive trend reporting on compliance issues, tracking open actions to ensure the business can actively evidence its compliance to global regulators.</li></ul> 
What you will need<ul><li>
2&ndash;3 years of experience as a Data Analyst, Risk Analyst, or Business Intelligence Engineer, ideally within a scaling Fintech, SaaS, or highly regulated operational environment.</li><li>
Strong proficiency in SQL (joins, CTEs, optimization) and experience building production-grade dashboards in BI tools (e.g., Tableau, Power BI, or Looker).</li><li>
Experience working with risk management platforms, GRC systems, or internal application development (experience with internal low-code/no-code internal app building is a massive plus).</li><li>
While you do not need to be a legal expert, you must be eager to learn cross-domain compliance areas like EOR regulations, marketing compliance, and global regulatory frameworks.</li><li>
Proven ability to operate in a fast-paced &quot;build&quot; environment, transforming unstructured, messy data into organized, automated pipelines.</li></ul></div>

Compliance Governance Data Scientist

The AA

<div><h3 class="jobSectionHeader">Company Description/ Business Unit</h3>
Location: London (hybrid working 3 office days per week)

Employment Type: Permanent, full time

Additional Benefits: Annual Bonus

Think the AA is just about roadside assistance? Think again.

For over a century, we've been evolving and adapting. Today, as the nation's leading motoring organisation, we offer a wide range of products and services to millions of customers. From roadside assistance to home and motor insurance, and the latest driving technologies, we have it all. As we continue to expand, diversify, and modernise, joining us as a Data Scientist means you'll play a crucial role in our success and be part of this exciting motoring journey.

Our Chief Operating Office (COO) are the backbone of The AA, providing both stability and structure to support growth and innovation. We are the drivers of change.

#LI-Hybrid<h3 class="jobSectionHeader">
This is the job</h3>
Data is one of the AA&rsquo;s biggest opportunities, and we are investing in the tools, platforms and AI capability to use it better. As a Data Scientist, you will help us turn complex data into practical solutions that improve how we forecast demand, optimise workforce deployment and support better decisions across our roadside operation.

This role is particularly focused on demand and supply forecasting, using machine learning to help ensure the right patrol capability is available in the right place at the right time. You will work on real operational challenges linked to national workforce planning, resource optimisation, customer demand, service levels and operational performance.

We are looking for someone who enjoys solving complex, real-world problems with data. You may have gained experience in organisations with large field-based, mobile or nationally deployed workforces, such as logistics, delivery, utilities, transport, airlines, emergency services, mobility or roadside operations. You will bring strong analytical thinking, practical data science capability and the confidence to translate technical insight into meaningful recommendations that help the business make better operational decisions.<h3 class="jobSectionHeader">
What will I be doing?</h3><ul>
<li>Build and deploy statistical models and machine learning solutions to support forecasting, product development, value driver analysis and operational performance.</li>
<li>Use data mining, modelling and algorithmic approaches, including AI and LLM-enabled techniques where appropriate, to solve complex business problems.</li>
<li>Work with data, engineering, architecture and AI Centre of Excellence colleagues to design and embed scalable algorithms into AA platforms, products and channels.</li>
<li>Analyse trends, evaluate scenarios, assess risks and uncover insight that supports better business and customer outcomes.</li>
<li>Explore, onboard and use relevant data sources, ensuring data is appropriate, reliable and aligned to good data governance practice.</li>
<li>Communicate findings clearly through presentations, workshops and stakeholder conversations, translating technical insight into meaningful business recommendations.</li>
</ul><h3 class="jobSectionHeader">What do I need?</h3>
We are looking for someone who can bring:
<ul>
<li>Experience applying data science, machine learning or advanced analytics to demand forecasting, supply forecasting, workforce planning or operational optimisation.</li>
<li>Strong capability in Python, SQL and statistical modelling, with experience building practical models that support business decision making.</li>
<li>Experience working with complex operational data, ideally linked to mobile workforces, field operations, logistics, transport, delivery, utilities, emergency services, airlines, mobility or roadside operations.</li>
<li>The ability to turn ambiguous operational challenges into clear analytical questions, scalable models and actionable recommendations.</li>
<li>Strong communication skills, with the confidence to explain complex analysis clearly to technical and non-technical stakeholders.</li>
<li>An understanding of responsible data use, data quality and governance, with exposure to Databricks, Git, Jira, ML Ops, feature stores or data pipelines being beneficial.</li>
</ul><h3 class="jobSectionHeader">Additional information</h3>
We&rsquo;re always looking to recognise and reward our employees for the work they do. As a valued member of The AA team, you&rsquo;ll have access to a range of benefits including:
<ul>
<li>25 days annual leave plus bank holidays + holiday buying scheme</li>
<li>Worksave pension scheme with up to 7% employer contribution</li>
<li>Free AA breakdown membership from Day 1 plus 50% discount for family and friends</li>
<li>Discounts on AA products including car and home insurance</li>
<li>Employee discount scheme that gives you access to a car salary sacrifice scheme plus great discounts on healthcare, shopping, holidays and more</li>
<li>Company funded life assurance</li>
<li>Diverse learning and development opportunities to support you to progress in your career</li>
<li>Dedicated Employee Assistance Programme and a 24/7 remote GP service for you and your family</li>
</ul>
Plus, so much more!

We&rsquo;re an equal opportunities employer and welcome applications from everyone. The AA values diversity and the difference this brings to our culture and our customers. We actively seek people from diverse backgrounds to join us and become part of an inclusive company where you can be yourself, be empowered to be your best and feel like you truly belong. We have five communities to bring together people with shared characteristics and backgrounds and drive positive change.

#LI-HH</div>

Data Scientist

LABOUR PARTY

<div></div><div><div><div><div><div><h2 class="jobSectionHeader">Job description</h2><div>
Role: Data Scientist
Salary: &pound;54,673.46 (gross) per annum inclusive of London Weighting, with a fixed sum allowance of &pound;1,195.
Current employees in banding 36 will maintain their existing salary.
Location: Head Office - London
Duration: Permanent 
The Labour Party is looking to recruit a Data Scientist. The post-holder will be responsible for supporting the work of the party in the analysis of voter behaviour, elections and campaigning, to contribute to Labour&rsquo;s political and organisational strategies through the use of data analysis, and lead on the measurement and reporting of campaign progress and campaign effects. 
The successful candidate will have: 
<ul><li>
Strong understanding of statistical modelling, with a minimum of degree-level statistical understanding, or equivalent professional experience</li><li>
Strong understanding of polling methodology and how to use to polling to answer political questions.</li><li>
Experience of conducting analysis and reporting on political data and polling and producing outputs like reports, visualisations and dashboards for stakeholders.</li><li>
Ability to understand how data on voters, campaigns and elections can be used to drive strategic decision making</li></ul> 
The Labour Party&rsquo;s standard working arrangement is that all employees based in headquarters in London/Newcastle attend their contracted office four days per week, Monday to Thursday. Home working is only authorised on Fridays. 
The deadline for applications is 12 July 2026. 
The Labour Party values equality and diversity, and welcomes applications from candidates regardless of sex, race, disability, age, sexual orientation, gender reassignment, religion or belief, marriage and civil partnership, or pregnancy and maternity.</div></div></div></div></div></div>

Goldman Sachs

<div>
 
 Job Description
 
 
 
 Are you a visionary Data Scientist or Machine Learning Scientist passionate about leveraging cutting-edge AI to transform financial markets? Do you thrive on building end-to-end solutions, from robust data pipelines and sophisticated feature engineering to deploying advanced predictive models and personalized recommendation systems? If you have hands-on experience, and a desire to make a significant impact in a dynamic, fast-paced environment, we want to hear from you.
 
 
 
 OUR IMPACT
 
 
 
 The Global Markets Division
 
 
 As a Data Scientist/Machine Learning Scientist in the Global Markets Division, you will be at the forefront of innovation on the trading floor. You will design and implement advanced machine learning models, including predictive AI, to uncover complex market trends and generate actionable insights
 
 .
 
 Leveraging cutting-edge techniques, you will develop sophisticated analytical tools that will, at scale, connect clients to the signals, tools and expertise to better analyze their portfolios and manage risk. Your expertise will drive data-driven product development and business strategy through advanced analytics, predictive modelling, and the application of recommendation systems. Our data scientists and machine learning engineers are applying advanced quantitative and AI/ML techniques to solve the most complex business challenges in a dynamic, entrepreneurial team with a passion for the markets.
 
 
 Marquee
 
 
 Marquee is Goldman Sachs' premier digital platform for Global Banking &amp; Markets, serving our Institutional Clients (Hedge Funds, Asset Managers, Insurers) and Corporate Clients with the latest insights and analytics from the division. A recognized market leader, Marquee has garnered 5 awards over the past 3 years for its innovative solutions.
 
 
 The Marquee Sales Strats Team
 
 
 The Marquee Sales Strats team is a hub for advanced data science and machine learning, focusing on developing and deploying predictive AI, recommendation systems, and sophisticated analytical models. We leverage extensive datasets, including those structured in graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee&rsquo;s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring, cutting-edge technology, and advanced data science/machine learning, including specialists in graph theory and knowledge representation.
 
 
 
 How You Will Fulfill Your Potential
 
 
 
 At Goldman Sachs, our Engineers and Scientists don&rsquo;t just make things &ndash; we make things possible. Change the world by connecting people and capital with ideas and technology. Combine advanced engineering and deep market knowledge to solve the most pressing problems for our clients. We look for creative collaborators who evolve, adapt to change, and thrive in a fast-paced global environment.
 
 
 As a Marquee Sales Data Scientist/Machine Learning Scientist, you will be instrumental in designing, developing, and deploying advanced machine learning models, including predictive AI and recommendation systems, to deliver unparalleled analytics and insights for the Goldman Sachs Franchise
 
 .
 
 Your work will directly enhance the client experience and drive strategic decision-making
 
 .
 
 You will collaborate closely with Traders, Salespeople, and Strats across all asset classes, leveraging your expertise to build robust data pipelines, engineer impactful features, and train sophisticated models. Your contributions will be critical in developing personalized recommendation engines and predictive analytics that drive Marquee platform adoption and ensure clients receive the most relevant, timely, and actionable content. You will utilize technologies including Python (Pandas, Polars, Scikit-learn, TensorFlow/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies.
 
 
 
 Responsibilities
 
 
 
 
 RESPONSIBILITIES AND QUALIFICATIONS:
 
 
 
 <ul>
 <li>
 Design, build, and maintain robust data pipelines for feature engineering and model training, ensuring data quality, scalability, and explainability.
 </li>
 <li>
 Develop, train, and deploy state-of-the-art machine learning models, with a strong focus on recommendation systems and signal generation, to address complex problems in financial markets.
 </li>
 <li>
 Utilize and contribute to the development of graph databases and knowledge graphs to enrich data context, uncover hidden relationships, and make predictions.
 </li>
 <li>
 Conduct rigorous model evaluation, A/B testing, and monitoring to ensure optimal performance, reliability, and business impact of deployed models.
 </li>
 <li>
 Collaborate with product managers, engineers, and business stakeholders to translate complex analytical findings into clear, actionable insights and integrate ML solutions into production systems.
 </li>
 <li>
 Stay abreast of the latest advancements in machine learning, AI, and data science, and proactively identify opportunities to apply new techniques.
 </li>
 <li>
 Contribute to the team's overall technical growth and best practices.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field.
 </li>
 <li>
 2+ years of proven expertise and hands-on experience in the full lifecycle of data science and machine learning projects, from data ingestion and feature engineering to model deployment and monitoring in a production environment.
 </li>
 <li>
 Exceptional programming skills in Python, with a command of data science libraries (e.g., Pandas, NumPy, Scikit-learn)
 </li>
 <li>
 Experience with big data technologies (e.g., Spark, Trino, Hadoop) and ideally cloud platforms (e.g., AWS, GCP, Azure) for scalable data processing, storage, and model deployment.
 </li>
 <li>
 Ideally having understanding and practical experience with graph databases (e.g., Neo4j, Amazon Neptune, ArangoDB) and knowledge graph construction, querying (e.g., Cypher, SPARQL), and utilization for feature enrichment.
 </li>
 <li>
 Strong understanding of statistical modeling, experimental design, and causal inference.
 </li>
 <li>
 Clear, critical thinking, concise writing skills, and excellent communication skills, with the ability to articulate complex technical concepts to diverse audiences.
 </li>
 <li>
 Self-starter with a creative, hands-on approach to problem-solving and a passion for designing and implementing programmatic solutions to client needs.
 </li>
 <li>
 Able to thrive in a global, fast-paced, and collaborative team environment.
 
 
 </li>
 </ul>
 
 About Goldman Sachs
 
 
 
 At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.
 
 
 We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.
 
 
 We&rsquo;re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
 
 
 &copy; The Goldman Sachs Group, Inc., 2023. All rights reserved.
 
 
 Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
</div>

Global Banking & Markets - Data / Machine Learning Scientist, Marquee Sales Strats, Associate

Experian

<div><div>Role Overview</div> 
Internal Grade D/EB8
Data Scientist &ndash; GenAI &amp; AI Engineering
The Generative AI Centre of Expertise (GenAI CoE) at Experian helps teams across Experian's UK business. It improves products using Generative AI, machine learning, and automation. The centre has a focus on responsible, measurable impact.
Who is a GenAI CoE Data Scientist?
This is a mid-level, hybrid role for a data scientist who enjoys hands-on work and wants to grow into AI engineering. You'll report into the Head of Machine Learning and work across two connected areas:<ul><li>
Experimentation and evaluation (data science): framing problems, designing experiments, defining success metrics, analysing results, and understanding model/system behaviour in product contexts</li><li>
AI engineering: build GenAI systems (prototypes through to production-ready components), supported by experienced colleagues</li></ul>
A big part of the job is choosing the right approach &mdash; when GenAI is valuable, and when simpler analytics or ML is the better answer.
What you'll do<ul><li>
You will work with product, engineering, and business teams to turn fuzzy ideas into clear problem statements, assumptions, and success metrics</li><li>
You will design and run experiments to evaluate GenAI systems, including baseline comparisons, error analysis, and understanding failure modes</li><li>
Help refine GenAI solutions, using modern development practices and AI-assisted coding tools to iterate quickly</li><li>
Communicate results, including trade-offs, limitations, and recommendations for what to do next</li><li>
Share insights with the team and spend ~10% of your time on learning and knowledge sharing</li></ul> 
 
<div>Experience and Skills</div> 
<ul><li>You have experience working as a data scientist (or in a similar role), applied machine learning, and Python programming.</li><li>
You are comfortable working with incomplete information, and enjoy figuring things out through exploration and experimentation.</li><li>
You are keen to develop broader skills across AI engineering and product-focused delivery.</li><li>
You think beyond your scope: you join up product, data, and engineering context to spot issues early and improve decisions.</li></ul> 
It would be great if you also have<ul><li>
Exposure to software engineering practices such as version control, testing, or object-oriented programming.</li><li>
You will understand how companies deploy or run AI systems in practice through cloud services or containerised environments.</li><li>
Experience explaining technical concepts or analysis to non-technical partners.</li></ul> 
 
<div>About Experian</div> 
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.
We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.
We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.
Benefits package includes:<ul><li>
Hybrid working - 40% office based</li><li>
Great compensation package and discretionary bonus plan</li><li>
Core benefits include pension, bupa healthcare, sharesave scheme and more!</li><li>
25 days annual leave with 8 bank holidays and 3 volunteering days. You can also purchase additional annual leave.</li></ul>
Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward &amp; recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces&trade; 2024 (Fortune Top 25), Great Place To Work&trade; in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.
Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
#LI-Hybrid #LI-ST1 
Experian Careers - Creating a better tomorrow together</div>

Data Scientist – GenAI & AI Engineering

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

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
We are hiring a Lead Data Scientist to drive the technical delivery of our most demanding AI engagements and to lead a growing team of data scientists and AI engineers. This role is for a practitioner who is equally fluent in the rigour of traditional data science (statistical modelling, machine learning, experimentation) and the fast-moving world of large language models and agentic AI. You understand that the best solutions often combine both.
You will own delivery from problem framing through to deployment, ensuring the work is technically sound, commercially valuable, and aligned to the architectural vision. As a lead, you will mentor the team, raise engineering and modelling standards, and act as a trusted technical partner in client conversations. You will help clients see not just what is possible, but what is practical and worth doing.
This is a delivery-focused leadership role with genuine breadth: one week you might be tuning a forecasting model, the next designing an agentic workflow or evaluating an LLM pipeline for a client pilot.
Required skills &amp; experience:<ul><li>
Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.</li><li>
Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.</li><li>
Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.</li><li>
Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.</li><li>
Ensure best practice across the AI lifecycle &mdash; experimentation, evaluation, testing, deployment, and monitoring.</li><li>
Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.</li><li>
Support pre-sales and client discussions with credible technical input and realistic estimation.</li><li>
Champion reproducibility, model governance, and responsible practice in everyday delivery.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.</li><li>
Strong foundations in machine learning and statistics, with demonstrable production experience.</li><li>
Practical experience with LLMs and generative AI &mdash; prompting, RAG, fine-tuning, and evaluation.</li><li>
Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.</li><li>
Proficiency in Python and the modern data / ML stack; sound data engineering instincts.</li><li>
Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).</li><li>
Experience supporting business development or pre-sales.</li><li>
Domain depth in a regulated or data-rich industry.</li><li>
Contributions to open source, publications, or a visible professional profile.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will lead substantive, end-to-end AI work in a practice that is scaling fast and backing its people to grow with it. You will shape how a team works, influence how clients adopt AI, and keep your own skills at the frontier, bridging proven data science with the most current GenAI and agentic techniques. It is an opportunity to lead, deliver, and keep building.</div>

Lead Data Scientist (Classical ML, LLMs & AI Agents)

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