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ai scientist

McKinsey & Company

<div><div><div><div><div><div><div>Job ID: 109890</div></div></div></div><div></div><div><ul><div>
London</div><div>
Madrid</div></ul></div><div></div><div><div><div><br>
</div></div></div></div><div><p>
Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You&rsquo;ve come to the right place.</p><div><p>
YOUR IMPACT</p><div><div>
You will be part of QuantumBlack Labs and the Robotics and Physical AI team within our Advanced Industries Sector, a group of engineers, scientists, product managers, and machine learning specialists building a first of its kind physics AI capability that accelerates and scales how the world designs and builds physical systems.</div><div></div><div>
Our team is responsible for:</div><div><ul><li>
Building multi-physics simulation frameworks, digital twins, and surrogate models that stand in for slow, expensive physics solvers</li><li>
Applying physics-informed machine learning and robotics to real-world engineering systems across advanced industries, from chip design to aircraft manufacturing</li><li>
Deploying scalable, production grade tools on HPC infrastructure that embed our distinctive technical approach and engineering knowledge for industrial clients</li></ul></div><div>
You will lead technical workstreams on client engagements, building multi-physics simulation frameworks and digital twins, developing surrogate and machine learning models, applying physics-informed machine learning to real-world engineering systems, deploying scalable production tools on HPC infrastructure, and translating computational insights into strategic recommendations and solutions that deliver measurable impact for clients.</div><div></div><div>
You&rsquo;ll create surrogate models that replace costly simulations, compress design cycles from weeks to minutes, and bring autonomy to robotic systems on the factory floor. Collaborating with global, multidisciplinary teams, you&rsquo;ll drive innovation, develop impactful technologies, and grow as a leader in physical AI.</div><div></div><div>
You will work with diverse and complex engineering data sets, develop scientific software products, and write optimized code to enhance our internal tools. Collaborating with scientists, engineers, and designers, you will leverage advanced math, statistics, and machine learning to deliver impactful solutions and grow the firm&rsquo;s capacity to deliver at scale.</div><div></div><div>
Your work will help clients address their most pressing challenges by deploying cutting-edge technology and amplifying impact across industries. You will also contribute to the broader physical AI community by writing papers, presenting at conferences, and sharing knowledge with colleagues.</div><div></div><div>
You will be based in London or Madrid and collaborate closely with scientists, data engineers, machine learning engineers, designers, and product managers around the world. Together, you&rsquo;ll work on interdisciplinary projects to solve complex engineering challenges across a range of industries, leading the development and application of cutting-edge physics AI solutions that drive measurable business impact.</div><div></div><div>
You&rsquo;ll grow as a technologist and leader in a collaborative, multidisciplinary environment, pushing the boundaries of innovation while shaping the future of physical AI and robotics.</div></div></div><div></div><div><p>
YOUR GROWTH</p><div><p>
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.</p><p></p><p>
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues&mdash;at all levels&mdash;will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won&rsquo;t find anywhere else.</p><p></p><p>
When you join us, you will have:</p><p></p><div><ul><li>
Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.</li><li>
A voice that matters: From day one, we value your ideas and contributions. You&rsquo;ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.</li><li>
Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm&rsquo;s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you&rsquo;ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.</li><li>
World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.</li></ul></div></div></div></div></div><div><div><div><p>
YOUR QUALIFICATIONS AND SKILLS</p><div><div><ul><p>
Advanced graduate degree (M.S. or Ph.D.) in computational mechanics, materials science, mechanical/aerospace/nuclear engineering, computational physics, or a closely related engineering or physical science field required; significant industry or national laboratory experience in applied simulation or scientific machine learning may apply.</p><p>
Demonstrated ability to develop high-quality engineering or scientific code (e.g., in Python, C++).</p><p>
Demonstrated fluency with statistical sampling, machine learning, and data science techniques.</p><p>
Simulation experience, PyTorch, ML/AI/Data Science a plus.</p><p>
Excellent organizational capabilities, including the ability to initiate tasks independently and see them through to completion.</p><p>
Proficient in rational decision-making based on data, facts, and logical reasoning.</p><p>
Ability to create work-product-focused materials / outputs, which may include PowerPoint decks, Excel models, articles, or other written deliverables.</p><p>
Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.</p><p>
Ability to work or attend meetings outside of traditional business hours or take on projects with limited or no notice at times.</p><p>
Ability to travel to and work in varying environments that may be challenging and/or not accessible (e.g., manufacturing facilities, etc.).</p><p>
Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels.</p></ul></div></div></div></div></div><div><div><div><div>
Please review the additional requirements regarding essential job functions of McKinsey colleagues.</div>
<div>Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.</div></div></div></div></div>

Physical AI Data Scientist - QuantumBlack Labs

Accenture

<div><p><b>YOU ARE</b></p><p>
As a Senior AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.</p><p></p><p>
Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree or equivalent</li></ul><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li><li>
Experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</li><li>
Experience in building and deploying AI/ML based software to a cloud environment.</li></ul><p><b>
PREFERRED QUALIFICATION</b></p><ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li><li>
MS or PhD in related field preferred (computer science, engineering, etc.)</li></ul></div><p></p>

AI/ML Computational Science Senior Manager

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact.<br>
<br>
Key job responsibilities<br>
<ul><li>Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale</li><li>Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning</li></ul>
- Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges<br>
<ul><li>Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale</li><li>Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact</li><li>Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability</li><li>Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements</li></ul><br>
About the team<br>
What is Amazon Strategic Account Services (SAS)?<br>
The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.
</div><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or a Master's degree and experience in building models for business application</li><li>Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact</li></ul><br>
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.<br>
<br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Applied Scientist II, Strategic Account Services (SAS)

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
We are looking for a passionate, talented, and inventive Data Scientist with a strong machine learning and analytics background to help build industry-leading language technology powering Alexa for Shopping, our AI-driven search and shopping assistant, helping customers with their shopping tasks at every step of their shopping journey.<br>
<br>
This innovative role focuses on developing conversation-based, multimodal shopping experiences, utilizing data analysis, statistical modeling, machine learning (ML) technologies, and experimentation to drive product decisions and optimize customer experiences.<br>
<br>
Our mission in conversational shopping is to make it easy for customers to find and discover the best products to meet their needs by helping with their product research, providing comparisons and recommendations, answering product questions, enabling shopping directly from images or videos, providing visual inspiration, and more. We do this by leveraging advanced analytics, Natural Language Processing (NLP), Machine Learning (ML), A/B testing, causal inference, and data-driven insights to continuously improve our systems.<br>
<br>
Key job responsibilities<br>
Key job responsibilities As a Data Scientist on our team, you will be responsible for the analysis, modeling, and optimization of AI technologies that will shape the future of shopping experiences. You will play a critical role in measuring and improving multimodal conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graphs, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include designing experiments, analyzing results, and launching new features, products and systems.<br>
<br>
A day in the life<br>
Perform hands-on analysis and modeling of enormous multimodal datasets to develop insights into how to best help customers throughout their shopping journeys. Use statistical methods, machine learning, and data mining techniques to create scalable solutions for measuring and optimizing shopping assistant systems based on a rich set of structured and unstructured contextual signals. Design and analyze A/B tests and experiments to evaluate new features and model improvements, ensuring statistical rigor and actionable insights. Develop metrics, dashboards, and reporting frameworks to monitor system performance, customer engagement, and business impact. Build predictive models and conduct deep-dive analyses to identify opportunities for improving customer experience, conversion, and satisfaction. Collaborate with Applied Scientists and Engineers to translate analytical insights into production systems, working closely on model evaluation and deployment. Establish automated processes for large-scale data analysis, ETL pipelines, metric generation, and experimentation frameworks. Communicate results and insights to both technical and non-technical audiences, including through presentations, written reports, and data visualizations.<br>
<br>
About the team<br>
The Alexa for Shopping Science team, based in London, works alongside ~150 engineers, designers and product managers, shaping the future of AI-driven shopping experiences at Amazon. The team works on every aspect of the AfS AI, from making it agentic, enabling customers to set price alerts or empower AfS to act on their behalf and automatically purchase products when the price is right, to understanding multimodal user queries and generating answers that combine text, image, audio and video, including deep research reports that scour the web and the Amazon catalog to provide detailed and personalised shopping guidance. We utilize and advance state-of-art techniques in the fields of Natural Language Processing, gen AI, Information Retrieval, Machine/Deep Learning, and Data Mining. We validate our work by actively participating in the internal and external scientific communities.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Master's degree or above in Math, Statistics, Computer Science, or related science field</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance</li><li>Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2</li><li>Experience working on multi-team, cross-disciplinary projects</li></ul><br>
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.<br>
<br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Data Scientist II, Alexa for Shopping Science UK, Alexa for Shopping Science UK

Elsevier

<div>
 <strong>
  Data Scientist
  <br/>
  <br/>
 </strong>
 <strong>
  AI for Science, Research Intelligence &amp; Knowledge Discovery
  <br/>
  <br/>
 </strong>
 <strong>
  Technology &ndash; Data Science Organization
  <br/>
  <br/>
 </strong>
 <strong>
  Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions?
  <br/>
  <br/>
 </strong>
 <strong>
  Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create real user value?
  <br/>
  <br/>
 </strong>
 <strong>
  Job Description
  <br/>
  <br/>
 </strong>
 <strong>
  About the team
  <br/>
  <br/>
 </strong>
 Elsevier&rsquo;s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics.
 <br/>
 <br/>
 This role sits within Elsevier&rsquo;s
 <strong>
  Platform Data Science organization
 </strong>
 , a centralized AI and data science group responsible for advancing intelligent discovery, retrieval, and generative AI capabilities across Elsevier products and platforms. The organization develops foundational AI technologies that power experiences such as
 <strong>
  LeapSpace
 </strong>
 , Elsevier&rsquo;s AI-powered research assistant, as well as Elsevier&rsquo;s broader
 <strong>
  Search &amp; AI Platform
 </strong>
 .
 <br/>
 <br/>
 The Platform Data Science organization works at the intersection of:
 <br/>
 <br/>
 <ul>
  <li>
   Search and retrieval systems
  </li>
  <li>
   Generative AI and LLM applications
  </li>
  <li>
   AI evaluation and experimentation
  </li>
  <li>
   Semantic enrichment and knowledge systems
  </li>
  <li>
   Scalable AI platforms and intelligent workflows
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 We are looking for a
 <strong>
  Data Scientist III
 </strong>
 to help design, build, and evaluate advanced AI capabilities supporting LeapSpace and Elsevier&rsquo;s Search &amp; AI Platform initiatives. This role focuses on
 <strong>
  applied AI development, retrieval systems, and AI evaluation
 </strong>
 , helping bring cutting-edge AI technologies into production experiences used by researchers worldwide.
 <br/>
 <br/>
 You will work closely with senior data scientists, engineers, product managers, and domain experts across
 <strong>
  retrieval systems, generative AI, reasoning workflows, evaluation frameworks, and experimentation
 </strong>
 , contributing to the next generation of AI-powered scientific discovery tools.
 <br/>
 <br/>
 This role is ideal for someone with hands-on experience in
 <strong>
  applied AI, NLP, information retrieval, and LLM-based applications
 </strong>
 , who enjoys building innovative solutions and translating emerging AI techniques into impactful product capabilities.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <strong>
  Applied AI &amp; Research
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop and improve LLM-powered research workflows, including:Scientific question answeringLiterature summarizationSemantic exploration and discoveryResearch insight generationCitation-aware retrieval and reasoning workflows
  </li>
  <li>
   Build and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tools.
  </li>
  <li>
   Apply modern techniques in:NLPGenerative AIEmbeddings and semantic representationsRetrieval-augmented generation (RAG)AI reasoning and workflow orchestration
  </li>
  <li>
   Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption.
  </li>
  <li>
   Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts.
  </li>
  <li>
   Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Search, Retrieval &amp; RAG Systems
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.
  </li>
  <li>
   Contribute to the development and enhancement of RAG systems that integrate LLMs with trusted scientific and biomedical content.
  </li>
  <li>
   Experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality.
  </li>
  <li>
   Support development of semantic search, ranking, and knowledge discovery capabilities.
  </li>
  <li>
   Collaborate with engineering teams to deploy and scale AI-powered solutions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  AI Evaluation &amp; Experimentation
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Develop and apply evaluation frameworks for search and AI systems, including:IR metrics (e.g., NDCG, recall, precision)LLM and RAG evaluation metrics (e.g., grounding, faithfulness, hallucination detection)
  </li>
  <li>
   Build and maintain evaluation datasets, benchmark suites, and annotation workflows.
  </li>
  <li>
   Conduct offline experiments and contribute to online experimentation and A/B testing.
  </li>
  <li>
   Analyze experimental results and communicate findings to stakeholders.
  </li>
  <li>
   Contribute to responsible AI practices focused on quality, reliability, and trust.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Cross-functional Collaboration
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Partner with product managers, engineers, UX researchers, and domain experts to deliver AI-powered capabilities.
  </li>
  <li>
   Communicate technical findings and recommendations clearly to both technical and non-technical audiences.
  </li>
  <li>
   Contribute to knowledge sharing and adoption of best practices across the Platform Data Science organization.
  </li>
  <li>
   Support delivery of projects from research and experimentation through production deployment.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master&rsquo;s or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field
  </li>
  <li>
   ~2&ndash;4 years of experience in data science, machine learning, applied NLP, information retrieval, generative AI, or a related field
  </li>
  <li>
   Hands-on experience with:LLM-based applications and generative AI systemsRAG pipelines and retrieval systemsSearch and retrieval architectures (lexical, vector, hybrid)Evaluation methodologies for IR and generative AI systems
  </li>
  <li>
   Strong programming skills in Python
  </li>
  <li>
   Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
  </li>
  <li>
   Experience working with Databricks or similar distributed data and machine learning platforms
  </li>
  <li>
   Understanding of experimentation methodologies, evaluation frameworks, and statistical analysis
  </li>
  <li>
   Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn)
  </li>
  <li>
   Demonstrated ability to independently execute technical projects and contribute to cross-functional initiatives
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience building AI assistants, agentic workflows, or conversational AI applications
  </li>
  <li>
   Experience working on search, ranking, recommendation, or retrieval systems
  </li>
  <li>
   Familiarity with scientific, biomedical, or scholarly datasets
  </li>
  <li>
   Experience with knowledge graphs, ontologies, or semantic enrichment systems
  </li>
  <li>
   Exposure to production ML systems and MLOps practices
  </li>
  <li>
   Academic or industry research experience in NLP, information retrieval, search, or generative AI
  </li>
  <li>
   Experience working in content-rich, knowledge-intensive, or highly regulated domains
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Working for you
  <br/>
  <br/>
 </strong>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
 <br/>
 <br/>
 <ul>
  <li>
   Comprehensive Pension Plan
  </li>
  <li>
   Home, office, or commuting allowance.
  </li>
  <li>
   Generous vacation entitlement and option for sabbatical leave
  </li>
  <li>
   Maternity, Paternity, Adoption and Family Care leave
  </li>
  <li>
   Flexible working hours
  </li>
  <li>
   Personal Choice budget
  </li>
  <li>
   Internal communities and networks
  </li>
  <li>
   Various employee discounts
  </li>
  <li>
   Recruitment introduction reward
  </li>
  <li>
   Employee Assistance Program (global)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About The Business
  <br/>
  <br/>
 </strong>
 As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world&rsquo;s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
 <br/>
 <br/>
 <strong>
  Together, we create possibilities. Join us.
  <br/>
  <br/>
 </strong>
 <strong>
  We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
 </strong>
</div>


Data Scientist II

Sainsbury’s

<div><div><h1 class="jobSectionHeader"><b>Senior Data Scientist
</b></h1></div><h4 class="jobSectionHeader"><b>Salary: </b><b>Competitive Plus Benefits</b><br>
<b>Location: </b><b>London Store Support Centre and Home, London, EC1M 6HA
</b><br>
<b>Contract type:
</b><br>
<b>Business area: </b><b>Data &amp; Analytics</b><br>
<b>Closing date: </b><b>07 July 2026</b><br>
<b>Requisition ID: </b><b>400067294</b></h4><p></p><div><div>At Sainsbury&rsquo;s, data sits at the heart of how we operate, innovate and serve our customers. Our Data &amp; Analytics team is building a technically advanced, commercially focused and impactful capability, powering our Next Level Strategy and helping to create a Sainsbury&rsquo;s powered by industry leading AI algorithms. We use data, technology and advanced analytics to drive better decisions across the business, from forecasting and optimisation to experimentation, personalisation and machine learning. With one of the richest retail datasets I n the UK and a portfolio spanning Sainsbury&rsquo;s, Argos, Habitat and Nectar, the opportunity to innovate is huge. Here, you&rsquo;ll tackle complex challenges at scale, create measurable impact and grow quickly alongside brilliant colleagues. People who thrive with us combine business understanding, technical expertise and curiosity, with a natural instinct for problem-solving. Join us and help shape the future of retail through data and AI.
</div></div><div><div><p><b>Senior Data Scientist &ndash; Nectar360</b></p><br>
<p></p>
<p><b>
Location</b></p>
<p>
London &ndash; Farringdon/Home</p>
<p><b>
Reporting to</b></p>
<p>
N360 Data Science Manager</p><br>
<p></p>
<p><b>
What is it?</b></p>
<p>
We&rsquo;re looking for a talented Senior Data Scientist to join Nectar360 &ndash; the team behind Sainsbury&rsquo;s Retail Media offering, and the UK&rsquo;s largest coalition loyalty programme (Nectar), with 24 million members nationwide.</p>
<p>
Our N360 Data Science team builds the systems behind our market-leading Retail Media platform (N360 Pollen), allowing hundreds of suppliers, media agencies and internal teams to set up, customise and measure their marketing campaigns. We develop and continuously improve our cutting-edge measurement capabilities, including multi-channel attribution, uplift estimation, AI-driven targeting and budget optimisation - across instore, onsite and offsite media. Our work enables suppliers to engage with customers every day and maximise the impact of their advertising.</p>
<p>
Based in our new Farringdon office, this role will work closely with decision-makers across Nectar360 and Sainsbury&rsquo;s to continue building innovative solutions for Nectar360, our suppliers and partners, using our incredible data assets, our rich customer understanding, and state of the art machine learning and AI. As one of the senior individual contributors in the team, you&rsquo;ll apply your wealth of experience and ideas to design, build, and improve our capabilities &ndash; driving value for the customer and the business. With a large team of data scientists and analysts across Sainsbury&rsquo;s and millions of known customers, the scale and scope are huge.</p><br>
<p></p>
<p><b>
What you will do</b></p>
<p>
As a Senior Data Scientist, your key responsibilities will include:</p>
<p>
Solve the hard problems</p>
<ul>
<li>Lead on the technical development of algorithms and pipelines that will deliver against our strategic objectives in Nectar360, including our industry-leading marketing measurement solutions.</li>
<li>Develop and enhance modelling and optimisation capabilities, using techniques such as MMMs, causal inference, multi-touch attribution, experimentation Bayesian modeling, unsupervised learning and many others.</li>
<li>Own projects, leading junior colleagues and engaging with stakeholders to define goals and ensure projects deliver impact.</li></ul><br>
<p></p>
<p>
Embody and improve best practice</p>
<ul>
<li>Align to best practice across modelling, experimentation, deployment, and model lifecycle management.</li>
<li>Coach through doing &ndash; pairing on code and demonstrating standards.</li></ul><br>
<p></p>
<p>
Be an enthusiastic member of our community</p>
<ul>
<li>Become the recognised data science technical expert in your team, bringing new ideas for future approaches, including state of the art techniques where appropriate.</li>
<li>Understand how our business really works and how data science can improve customer experience and our offering to 3rd parties.</li>
<li>Actively contribute to our vibrant Data and Analytics community of over 800 colleagues</li></ul><br>
<p></p>
<p><b>
Who you are</b></p>
<p>
We&rsquo;re looking for a highly motivated self-starter &ndash; someone who fixes problems and creates value without micromanagement. You need to know how to balance our need for technical rigour against our need to deliver commercial and customer value.</p>
<p>
Value delivery</p>
<ul>
<li>Extensive experience in Data Science roles in a commercial setting, with evidence of solving complex problems end-to-end.</li>
<li>A record of building systems which run in production, and an understanding of the value these generated.</li>
<li>An ability to understand commercial reality as well as technical rigour, and a pragmatic mindset.</li>
<li>Experience working in an Agile way, and ability to understand the trade-off between immediate value, future value, and technical options.</li>
<li>A strong ability to communicate ideas to audiences of varying technical background and seniority, and present key ideas and insights succinctly.</li>
<li>Independence in proposing and implementing solutions</li></ul><br>
<p></p>
<p>
Data Science expertise</p>
<ul>
<li>Solid grounding and experience in applying statistical modelling and machine learning in commercial settings, with proven experience in some of the following areas: Causal inference, MMMs, Bayesian inference, experimentation, multi-touch attribution, time series modelling.</li>
<li>Ability to select the right technique for a given objective and avoid pitfalls.</li>
<li>Curiosity, scepticism and attention to detail regarding data quality, samples, bias and ethics.</li></ul><br>
<p></p>
<p>
Production-grade design</p>
<ul>
<li>Advanced programming ability in Python and strong ability to use SQL, with a proven experience of developing complex solutions and working with large codebases as part of a team.</li>
<li>Solid understanding of setting up and working with production codebases, version control and CI/CD.</li>
<li>Practical experience working with cloud platforms and MLOps tools to build and maintain production-ready solutions.</li>
<li>Ability to lead technical conversations with Data/ML Engineers.</li></ul><br>
<p></p>
<p>
Development and coaching</p>
<ul>
<li>A strong awareness and understanding of technology trends and direction in Data Science, analytics and AI.</li>
<li>Ability to support in the development, training and mentoring of others</li></ul><br>
<p></p>
<p><b>
Essential Criteria</b></p>
<ul>
<li>Extensive experience in previous Data Science roles in a commercial setting</li>
<li>A record of building systems which run in production</li>
<li>A strong ability to communicate ideas to audiences of varying technical background and seniority</li>
<li>Independence in proposing and implementing solutions</li>
<li>Solid grounding and experience in applying statistical modelling and machine learning in commercial settings</li>
<li>Advanced programming ability in Python and strong ability to use SQL</li>
<li>Solid understanding of working with production codebases, version control and CI/CD.</li></ul><br>
<p></p>
<p><b>
Support we will provide</b></p>
<ul>
<li>A vibrant team to bounce ideas off and to support you with specialised knowledge (technical, stats/data science or business processes)</li>
<li>Mentoring from Data Science Managers</li>
<li>Automation and orchestration support from our integrated engineering and product teams within Nectar360</li>
<li>Technical and non-technical training and regular hackathons, learning days and knowledge sharing sessions.</li></ul><br>
<p></p>
<p>
We are committed to being a truly inclusive retailer so you&rsquo;ll be welcomed whoever you are and wherever you work. Around here, there&rsquo;s always the chance to try something new &mdash; whether that&rsquo;s as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we&rsquo;ll also offer you an amazing range of benefits. Please see www.sainsburys.jobs for details.</p><br>
<p></p>
<p>
#DataAndAnalytics</p>
<p>
#DataScience</p>
<p>
#LI-CM1</p>
</div></div><div><div><p>We are committed to being a truly inclusive retailer so you&rsquo;ll be welcomed whoever you are and wherever you work. Around here, there&rsquo;s always the chance to try something new &mdash; whether that&rsquo;s as part of an evolving team or somewhere else across the business - and we take development seriously and promise to support you. We also recognise and celebrate colleagues when they go the extra mile and, where possible, offer flexible working. When you join our team, we&rsquo;ll also offer you an amazing range of benefits. Here are some of them: Starting off with colleague discount, you'll be able to save 10% on your shopping online and instore at Sainsbury's, Argos, TU and Habitat, and we regularly increase the discount to 15% at points during the year. We've also got you covered for your future with our pensions scheme and life cover. You'll also be able to share in our success as you may be eligible for a performance-related bonus of up to 20% of salary, depending on how we perform. Your wellbeing is important to us too. You'll receive an annual holiday allowance, and you can buy up to an additional week's holiday, and we provide private healthcare. We also offer other benefits that will help your money go further such as season ticket loans, interest free car loan of up to &pound;10k, cycle to work scheme, health cash plans, salary advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an Employee Assistance Programme. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks&rsquo; pay for maternity or adoption leave and up to 4 weeks&rsquo; pay for paternity leave. Please see www.sainsburys.jobs for a range of our benefits (note, length of service and eligibility criteria may apply).&quot;</p></div></div></div><p></p>

Senior Data Scientist

Experian

<div><div>Role Overview</div><br>
<p>Internal Grade D/EB8</p><p><b>
Data Scientist &ndash; GenAI &amp; AI Engineering</b></p><p>
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.</p><p><b>
Who is a GenAI CoE Data Scientist?</b></p><p>
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:</p><ul><li><b>
Experimentation and evaluation (data science):</b> framing problems, designing experiments, defining success metrics, analysing results, and understanding model/system behaviour in product contexts</li><li><b>
AI engineering:</b> build GenAI systems (prototypes through to production-ready components), supported by experienced colleagues</li></ul><p>
A big part of the job is choosing the <i>right</i> approach &mdash; when GenAI is valuable, and when simpler analytics or ML is the better answer.</p><p><b>
What you'll do</b></p><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><br>
<br>
<div>Experience and Skills</div><br>
<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><p></p><p><b><br>
It would be great if you also have</b></p><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><br>
<br>
<div>About Experian</div><br>
<p>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.</p><p>
We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.</p><p>
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.</p>
<p>Benefits package includes:</p><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><p>
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.</p><p>
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.</p><p>
#LI-Hybrid #LI-ST1</p><p></p><p><br>
Experian Careers - Creating a better tomorrow together</p></div><p></p>

Data Scientist – GenAI & AI Engineering

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