Global AI Legislation Content Optimisation Lead

Data & ML Architect

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Director, Data Science

Senior Manager Data Science

Manager, Data Science (GNS)

Role Description: <ul><li>This is a strategic individual contributor role within the Global Editorial Operations (GEO) team, responsible for driving AI-enabled transformation across legislative and regulatory content. </li><li>The successful candidate will partner closely with Editorial, Product and Technology teams to identify opportunities where AI and Large Language Models (LLMs) can improve content creation, enrichment, summarisation, classification, quality and workflow efficiency at a global scale.&nbsp;</li><li>While experience within legal or legislative publishing would certainly be advantageous, the hiring team is equally interested in professionals who have successfully led AI-enabled workflow optimisation and editorial transformation initiatives in publishing, information services, knowledge management or other content-rich environments.</li></ul> Responsibilities: AI Strategy &amp; Transformation&nbsp; <ul><li>Develop the global strategy for AI-enabled content creation and optimisation.</li><li>Identify opportunities to leverage LLMs, NLP and automation across editorial workflows.</li><li>Lead AI transformation initiatives from concept through implementation.</li></ul> Cross-functional Collaboration&nbsp; <ul><li>Partner with Product, Technology and Editorial teams to deliver scalable AI solutions.</li><li>Drive adoption of AI-enabled tools and new ways of working across global teams.</li><li>Influence stakeholders without direct line management responsibility.</li></ul> Editorial Excellence&nbsp; <ul><li>Define standards for AI-generated and AI-assisted content.</li><li>Ensure quality, consistency and responsible AI practices across editorial operations.</li><li>Develop best practices and training to improve AI capability across the organisation.</li></ul> Requirements: <ul><li>Experience leading AI or Generative AI workflow transformation.</li><li>Strong Editorial, Content Operations or Publishing background.</li><li>Experience implementing LLMs, NLP or AI-driven content solutions.</li><li>Programme or Product Management experience within content-rich environments.</li><li>Excellent stakeholder management and cross-functional leadership skills.</li><li>Legal, regulatory or legislative publishing experience is advantageous but not essential.</li></ul>

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</li></ul>

Responsibilities: <ul><li>Lead experimentation and model development for AI/ML solutions in legal products.</li><li>Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Proven experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Able to analyze large-scale legal datasets to extract insights and improve model performance.</li></ul>

Responsibilities: <ul><li>Develop and implement NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Develop retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Education: Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Strong experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Strong foundation in statistics, modeling, and large-scale text processing.</li></ul>

Responsibilities: Strategic Leadership:&nbsp; <ul><li>Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li></ul> Team Management:&nbsp; <ul><li>Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li></ul> Advanced Research Direction:&nbsp; <ul><li>Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li></ul> Machine Learning and AI Solutions:&nbsp; <ul><li>Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li></ul> Data Collection and Preparation:&nbsp; <ul><li>Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li></ul> Data Visualization Strategy:&nbsp; <ul><li>Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li></ul> Cross-functional Collaboration:&nbsp; <ul><li>Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li></ul> Model Deployment and MLOps:&nbsp; <ul><li>Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li></ul> Documentation Standards:&nbsp; <ul><li>Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li></ul> Budget and Resource Management:&nbsp; <ul><li>Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li></ul> Ethical AI Governance:&nbsp; <ul><li>Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</li></ul>

Responsibilities: <ul><li>Strategic Leadership: Define and execute the data science vision and roadmap aligned with business objectives and technological advancement opportunities.</li><li>Team Management: Build, lead, and mentor a high-performing team of data scientists, fostering a culture of innovation, collaboration, and continuous learning.</li><li>Advanced Research Direction: Direct cutting-edge research initiatives in NLP, LLMs, and other emerging AI technologies to maintain competitive advantage.</li><li>Machine Learning and AI Solutions: Lead the development and implementation of machine learning algorithms and AI solutions to solve complex business problems.</li><li>Data Collection and Preparation: Establish protocols for collecting, cleaning, and preprocessing large datasets, ensuring data quality and reliability.</li><li>Data Visualization Strategy: Guide the creation of informative and compelling data visualizations to communicate results and insights to stakeholders effectively.</li><li>Cross-functional Collaboration: Partner with executive leadership and cross-functional teams to identify strategic opportunities and address business challenges.</li><li>Model Deployment and MLOps: Oversee the deployment of machine learning models into pro duction environments, ensuring scalability and reliability.</li><li>Documentation Standards: Establish comprehensive documentation standards for projects, models, and code for knowledge sharing and reproducibility.</li><li>Budget and Resource Management: Manage departmental budget, resource allocation, and infrastructure needs for data science operations.</li><li>Ethical AI Governance: Develop and enforce ethical guidelines and best practices for AI development and deployment.</li></ul> Requirements: <ul><li>Bachelors, Masters or Ph.D. in Data Science, Computer Science, Statistics, or a related field; MBA or additional business education is a plus.</li><li>10+ years of progressive experience in data science, machine learning, or AI, with at least 8 years in leadership positions.</li><li>Demonstrated experience in managing and scaling data science teams of 15+ professionals.</li><li>Proven record of delivering high-impact AI and ML solutions that have driven significant business value.</li><li>Deep expertise with generative AI models and techniques (e.g., LLMs, GANs) for content generation and their practical applications.</li><li>Advanced knowledge of statistical analysis, machine learning algorithms, and data manipulation techniques at enterprise scale.</li><li>Experience in setting technical direction and implementing MLOps practices for model deployment and monitoring.</li><li>Strong business acumen with the ability to translate complex technical concepts into business value.</li><li>Excellent communication and leadership skills, with experience presenting to executive leadership.</li><li>Experience working in a global or multicultural environment.</li><li>Record of successful collaboration with product, engineering, and business teams.</li><li>Proficiency in multiple programming languages relevant to data science (Python, R, etc.) and big data technologies.</li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions</li><li>Lead the development of AI and machine learning models to solve business problems</li><li>Research, build, and deploy models based on shallow and deep machine learning</li><li>Train robust NLP-based models on large datasets</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs</li><li>Design APIs for disseminating data science outputs</li><li>Oversee the scaling of production systems to meet growing demands</li></ul> Requirements: <ul><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

Responsibilities: <ul><li>Manage a team of data scientists and engineers to design, develop, and deploy advanced AI solutions.</li><li>Lead the development of AI and machine learning models to solve business problems.</li><li>Research, build, and deploy models based on shallow and deep machine learning.</li><li>Train robust NLP-based models on large datasets.</li><li>Collaborate with cross-functional teams to align AI solutions with business goals and customer needs.</li><li>Design APIs for disseminating data science outputs.</li><li>Oversee the scaling of production systems to meet growing demands.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices.</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions.</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high-bar for model development.</li></ul> Requirements: <ul><li>Have substantial experience in a senior data scientist role.</li><li>Have experience in leading complex projects and customer relationships.</li><li>Have significant experience in managing larger Technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li></ul> Highly Desired Skills and Experience: <ul><li>PhD or Masters degree in Computer Science, Mathematics, Statistics, or a related field.</li><li>7-10+ years of experience in AI and machine learning.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li><li>Strong problem-solving skills and the ability to think outside the box. </li></ul>

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8 nlp Jobs found

Global AI Legislation Content Optimisation Lead

Data & ML Architect

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Director, Data Science

Director, Data Science

Senior Manager Data Science

Manager, Data Science (GNS)

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8 nlp Jobs found

Global AI Legislation Content Optimisation Lead

Data & ML Architect

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Director, Data Science

Director, Data Science

Senior Manager Data Science

Manager, Data Science (GNS)

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow is on a mission to connect companies with the best talent across the globe.