ai research scientist

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</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. 
 
Key job responsibilities 
<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 
<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> 
About the team 
What is Amazon Strategic Account Services (SAS)? 
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">BASIC QUALIFICATIONS</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">
PREFERRED QUALIFICATIONS</h2><ul><li>Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact</li></ul> 
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. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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)

Accenture

<div>YOU ARE
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.
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.
THE WORK<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>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<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>
PREFERRED QUALIFICATION<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 Senior Manager

<div>YOU ARE
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.
THE WORK<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>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<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>
PREFERRED QUALIFICATION<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>
 
 
 Department:
 
 Data &amp; AI
 
 
 
 Location:
 
 UK - London
 
 
 
 
 Description
 
 
 
 Insurance isn't the first industry most people think of when they imagine interesting data science work. That's exactly why this role is interesting.
 
 
 CFC's Data &amp; AI unit is building production agentic systems that automate complex underwriting decisions - not demos, not proof-of-concepts sitting on a shelf, but AI agents and Machine Learning (ML) pipelines that drive real business outcomes. The team includes machine learning engineers and software engineers shipping production services, and this role sits alongside them as an analytical counterpart: running experiments, stress-testing assumptions, and generating the evidence that shapes what gets built and how it improves over time.
 
 
 This is an Associate Data Scientist role designed for someone early in their career who wants genuine exposure to production AI systems from day one. You'll work closely with ML and AI engineers, contributing to discovery work that feeds directly into live services - statistical analysis, feature engineering, LLM evaluation, and the kind of careful, evidence-based thinking that makes the difference between an AI system that works in a notebook and one that holds up under real conditions.
 
 
 The problems are genuinely hard. The data is complex, the decisions are high-stakes, and the domain has the kind of depth that keeps the work interesting. If you want to grow quickly in applied AI and ML - working on real systems, not toy datasets - this is the right environment.
 
 
 
 About the role
 
 
 
 <ul>
 <li>
 Design and run experiments that directly shape production AI agents &mdash; testing ideas, validating approaches, and turning research into deployed improvements.
 </li>
 <li>
 Actively explore cutting-edge developments in AI and machine learning &mdash; with the space and support to experiment, prototype, and bring new techniques into production where they add value.
 </li>
 <li>
 Evaluate and refine LLM-powered workflows &mdash; building robust evaluation frameworks, stress-testing agent behaviour, and driving continuous quality improvements in live systems.
 </li>
 <li>
 Explore complex, real-world datasets to uncover insights that meaningfully improve underwriting decisions and system performance at scale.
 </li>
 <li>
 Prototype and iterate on features for AI/ML pipelines, taking ideas from early exploration through to measurable impact in production services.
 </li>
 <li>
 Investigate how agentic systems behave in production &mdash; identifying edge cases, failure modes, and opportunities to make systems more robust and reliable.
 </li>
 <li>
 Collaborate closely with ML/AI engineers to bridge research and production &mdash; contributing code, debugging issues, and helping ship improvements end-to-end.
 </li>
 <li>
 Document experiments, findings, and methodologies clearly so that insights are reproducible and decisions are traceable.
 
 
 </li>
 </ul>
 
 About you
 
 
 
 We are looking for a Junior Data Scientist who enjoys solving complex problems and turning data into meaningful, real‑world outcomes. In this role, you will work across the full analytical lifecycle, from exploring data and building machine learning models to shaping how insights are communicated and applied across the business. You also play a part in how we responsibly explore and apply emerging technologies such as LLMs, focusing on how they perform and deliver value in practice.
 
 
 You:
 <ul>
 <li>
 combine a strong grounding in statistics with hands‑on technical capability in Python and SQL
 </li>
 <li>
 take pride in producing clear, reliable analysis
 </li>
 <li>
 are thoughtful and detail‑driven, able to communicate effectively with a wide range of stakeholders, and comfortable learning from others while growing your own ownership
 </li>
 <li>
 bring curiosity, ask the right questions and look beneath the surface
 </li>
 <li>
 have experience with Azure, MLflow, or LLM tooling is a bonus, but not expected&mdash;we value mindset and approach just as highly as experience.
 
 
 </li>
 </ul>
 
 Core Values
 
 
 
 
 Love what you do:
 
 
 We show up each day ready to take on the world. Our passion and intensity set us apart and makes the difference to our colleagues, customers, brokers and carriers.
 
 
 
 Challenge everything:
 
 
 We&rsquo;re never afraid to question the way that things are done and we constantly challenge ourselves and others to makes things better.
 
 
 
 Have fun, be good:
 
 
 Insurance is a serious business, but we don&rsquo;t take ourselves too seriously. We make it fun to work at CFC, we welcome all viewpoints, and we treat everyone how we would expect to be treated.
</div>

Associate Data Scientist

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

<div><h3 class="jobSectionHeader">Description</h3><div> 
Insurance isn't the first industry most people think of when they imagine interesting data science work. That's exactly why this role is interesting.</div><div>
 
CFC's Data &amp; AI unit is building production agentic systems that automate complex underwriting decisions - not demos, not proof-of-concepts sitting on a shelf, but AI agents and Machine Learning (ML) pipelines that drive real business outcomes. The team includes machine learning engineers and software engineers shipping production services, and this role sits alongside them as an analytical counterpart: running experiments, stress-testing assumptions, and generating the evidence that shapes what gets built and how it improves over time.</div><div>
 
This is an Associate Data Scientist role designed for someone early in their career who wants genuine exposure to production AI systems from day one. You'll work closely with ML and AI engineers, contributing to discovery work that feeds directly into live services - statistical analysis, feature engineering, LLM evaluation, and the kind of careful, evidence-based thinking that makes the difference between an AI system that works in a notebook and one that holds up under real conditions. 
</div><div>The problems are genuinely hard. The data is complex, the decisions are high-stakes, and the domain has the kind of depth that keeps the work interesting. If you want to grow quickly in applied AI and ML - working on real systems, not toy datasets - this is the right environment.</div><h3 class="jobSectionHeader"> 
About the role</h3> 
<ul>
<li>
Design and run experiments that directly shape production AI agents &mdash; testing ideas, validating approaches, and turning research into deployed improvements.</li>
<li>Actively explore cutting-edge developments in AI and machine learning &mdash; with the space and support to experiment, prototype, and bring new techniques into production where they add value.</li>
<li>Evaluate and refine LLM-powered workflows &mdash; building robust evaluation frameworks, stress-testing agent behaviour, and driving continuous quality improvements in live systems.</li>
<li>Explore complex, real-world datasets to uncover insights that meaningfully improve underwriting decisions and system performance at scale.</li>
<li>Prototype and iterate on features for AI/ML pipelines, taking ideas from early exploration through to measurable impact in production services.</li>
<li>Investigate how agentic systems behave in production &mdash; identifying edge cases, failure modes, and opportunities to make systems more robust and reliable.</li>
<li>Collaborate closely with ML/AI engineers to bridge research and production &mdash; contributing code, debugging issues, and helping ship improvements end-to-end.</li>
<li>Document experiments, findings, and methodologies clearly so that insights are reproducible and decisions are traceable.</li></ul> 
<h3 class="jobSectionHeader">
About you</h3><div> 
We are looking for a Junior Data Scientist who enjoys solving complex problems and turning data into meaningful, real‑world outcomes. In this role, you will work across the full analytical lifecycle, from exploring data and building machine learning models to shaping how insights are communicated and applied across the business. You also play a part in how we responsibly explore and apply emerging technologies such as LLMs, focusing on how they perform and deliver value in practice. 
 
You:</div><ul>
<li>combine a strong grounding in statistics with hands‑on technical capability in Python and SQL</li>
<li>take pride in producing clear, reliable analysis</li>
<li>are thoughtful and detail‑driven, able to communicate effectively with a wide range of stakeholders, and comfortable learning from others while growing your own ownership</li>
<li>bring curiosity, ask the right questions and look beneath the surface</li>
<li>have experience with Azure, MLflow, or LLM tooling is a bonus, but not expected&mdash;we value mindset and approach just as highly as experience.</li></ul> 
<h3 class="jobSectionHeader">
Core Values</h3><div> 

Love what you do: 
We show up each day ready to take on the world. Our passion and intensity set us apart and makes the difference to our colleagues, customers, brokers and carriers. 
 
Challenge everything: 
We&rsquo;re never afraid to question the way that things are done and we constantly challenge ourselves and others to makes things better. 
 
Have fun, be good: 
Insurance is a serious business, but we don&rsquo;t take ourselves too seriously. We make it fun to work at CFC, we welcome all viewpoints, and we treat everyone how we would expect to be treated.</div><h3 class="jobSectionHeader"> 
About CFC</h3><div>
CFC is a specialist insurance provider, pioneering emerging risk and market leader in cyber. Our global insurance platform uses cutting-edge technology and data science to deliver smarter, faster underwriting and protect customers from today's most critical business risk. 
</div><div>Headquartered in London with offices in New York, Melbourne, Sydney, Austin, Madrid, Brussels and Brisbane, CFC has over 1100 staff and is trusted by more than 100,000 businesses across 90 countries. 
</div><div>At CFC, insurance isn't just about underwriting. From data science to software development, and digital marketing design, we've got something for everyone. We're passionate about pushing boundaries, thinking differently and building the insurance company of the future. 
 
CFC is committed to the principles of equal opportunities and creating an environment in which all individuals are always treated with dignity and respect. We encourage a diverse corporate culture of openness and appreciation to create an environment in which your talent can be developed in the best possible way. Should you require any reasonable adjustments at any stage of the recruitment process please let us know.</div></div>

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Reporting to: Re &amp; ILS Head of Data
 
 
 
 
 Location:
 
 London
 
 
 Type: Permanent
 
 
 
 Role Overview
 
 
 
 The Lead Data Scientist is a crucial member of the
 
 extended
 
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 
 Data Science and Machine Learning
 
 chapter.
 
 
 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).
 
 
 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
 
 hands-on
 
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 
 
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 
 Group AI Governance Framework
 
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 
 
 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.
 
 
 
 About Hiscox Re &amp; ILS
 
 
 
 Hiscox Re &amp; ILS is located in
 
 Bermuda and London
 
 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.
 
 
 
 Key Responsibilities
 
 
 
 <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.
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 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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 </ul>
 
 Required Experience And Structure
 
 
 
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 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).
 
 
 
 </li>
 </ul>
 
 Candidate Profile
 
 
 
 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.
 
 
 
 Main Experience Required Is
 
 
 
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 <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.
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 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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 ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
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 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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 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.
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 Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
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 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.
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 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>
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 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.
 
 
 
 </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.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Lead Data Scientist

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