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)

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

<div><p><b>YOU ARE</b></p><p>
As an 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>

AI/ML Computational Science Assoc Manager

<div><p><b>YOU ARE</b></p><p>
As an 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. 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>

AI/ML Computational Science Manager

Hiscox

<div>
 <strong>
  Job Type
  <br/>
  <br/>
 </strong>
 Permanent
 <br/>
 <br/>
 <strong>
  Build a brilliant future with Hiscox
  <br/>
  <br/>
 </strong>
 <strong>
  Reporting to: Re &amp; ILS Head of Data
  <br/>
  <br/>
 </strong>
 <strong>
  Location:
 </strong>
 London
 <br/>
 <br/>
 Type: Permanent
 <br/>
 <br/>
 <strong>
  Role Overview
  <br/>
  <br/>
 </strong>
 The Lead Data Scientist is a crucial member of the
 <strong>
  extended
 </strong>
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 <strong>
  Data Science and Machine Learning
 </strong>
 chapter.
 <br/>
 <br/>
 This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).
 <br/>
 <br/>
 You will co-lead the new Data Science chapter with the RE&amp;ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&amp;ILS strategic Value Streams. Whilst the chapter grows, you are expected to be
 <strong>
  hands-on
 </strong>
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 <br/>
 <br/>
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 <strong>
  Group AI Governance Framework
 </strong>
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 <br/>
 <br/>
 This is likely to be your first managerial role and the first time you have had one or more direct reports &ndash; having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders &ndash; Head of Data and the Hiscox Group Head of Data Science as well.
 <br/>
 <br/>
 <strong>
  About Hiscox Re &amp; ILS
  <br/>
  <br/>
 </strong>
 Hiscox Re &amp; ILS is located in
 <strong>
  Bermuda and London
 </strong>
 and underwrites reinsurance risks from around the world on behalf of our own and other people&rsquo;s capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Chapter Leadership &amp; Talent Management
  </li>
  <li>
   People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture.
  </li>
  <li>
   In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths.
  </li>
  <li>
   Culture &amp; Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members.
  </li>
  <li>
   Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice.
  </li>
  <li>
   Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn &ndash; especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value.
  </li>
  <li>
   Solution Delivery &amp; ML Ops Excellence
  </li>
  <li>
   Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions.
  </li>
  <li>
   ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour.
  </li>
  <li>
   Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast &ndash; as a lot of AI use cases will be highly experimental in nature with no guarantees of success.
  </li>
  <li>
   Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models.
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   Strategy, Governance &amp; Innovation
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   Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains.
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   Governance &amp; Compliance: Champion data and model governance, working within the Group AI Governance Framework. Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work.
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   Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&amp;D to deliver reliable insights and potential next steps quickly.
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   Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership.
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 <strong>
  Required Experience And Structure
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 </strong>
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  <li>
   Reporting: Reports into the RE&amp;ILS Head of Data with a dotted line into the new Group Head of Data Science.
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   Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&amp;ILS Data Science Chapter.
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   Key Partners: RE&amp;ILS CTO, Group Head of Data Science, RE&amp;ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft).
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  </li>
 </ul>
 <strong>
  Candidate Profile
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 </strong>
 The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards. You will have a strong determination and resilience and not fear failure or the inevitable setbacks often found in highly experimental work.
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 <strong>
  Main Experience Required Is
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 </strong>
 <ul>
  <li>
   Deep Interest in Leadership: As an experienced data scientist or machine learning engineer, has previously demonstrated excellent traits in mentoring and coaching more junior team members and has been happy to invest in them - clearly demonstrating they care about other peoples&rsquo; career progression. Also you can evidence some successful business outcomes that you personally drove forward using advanced Data Science/AI &ndash; as this most likely is your first leadership role.
  </li>
  <li>
   Technical Depth: Extensive "hands-on" experience in architecting, designing, and building complex ML models, with a strong understanding of cloud services and the AI/ML/LLM ecosystem.
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  <li>
   ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
  </li>
  <li>
   AI and Data Governance: Mature understanding of AI and Data governance - data obfuscation &amp; data privacy laws, data version control, data lineage, and the application of AI governance frameworks in a regulated environment.
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  <li>
   Stakeholder Management: Experience in managing and driving collaboration with business unit leaders (Underwriters, pricing teams, MI team) and external technology partners like Google Cloud, Snowflake, DataIku and Microsoft.
  </li>
  <li>
   Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
  </li>
  <li>
   Capacity for independent, high-quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill-defined and challenging business problems.
  </li>
  <li>
   Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures.
  </li>
  <li>
   Real world experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), AI Agents and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.
  </li>
  <li>
   Demonstrate a Solid understanding of foundational statistics and experimental design. Pioneer the development and robust deployment of highly impactful machine learning and AI-driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization.
  </li>
  <li>
   Ability to translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real-world adoption and beneficial outcomes of our analytical work.
  </li>
  <li>
   Ability to elevate the technical maturity and capabilities of the data science chapter by shaping and implementing industry-leading AI, data, and analytics techniques, methodologies, and engineering best practices.
  </li>
  <li>
   Educator: shown the ability to train and coach more junior and mid-level team members - ensuring they have excellent career progression and become high performers.
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  </li>
 </ul>
 If you are a visionary expert looking for your first leadership role and ready to accelerate our value delivery and champion all things Data Science and AI, we invite you to apply for the position of Lead Data Scientist at Hiscox Re &amp; ILS. Join our team and be a catalyst for AI adoption in a dynamic, forward-thinking organization.
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  Work with amazing people and be part of a unique culture
 </em>
</div>


Lead Data Scientist

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