The Data And AI Podcast

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About the Role

As a Paid Media Associate, you will support the execution and optimization of digital marketing campaigns across search, social, and programmatic channels. You’ll work closely with senior team members and cross-functional strategists to help deliver high-performing campaigns, with hands-on exposure to platforms like Google Ads and Meta Ads Manager.

This is a great opportunity for someone early in their career to develop strong performance marketing skills while contributing to impactful client work.

Responsibilities include but are not limited to:

• Assist in the setup, execution, and optimization of paid media campaigns across search (SEM) and paid social (Meta, TikTok, etc.)
• Support campaign management in platforms such as Google Ads (Search, Shopping, YouTube) and Meta Ads Manager
• Monitor campaign performance and help identify opportunities for optimization and improvement
• Pull and analyze campaign data, contributing to reporting and performance insights
• Collaborate with internal teams to support integrated marketing campaigns across multiple channels
• Help maintain campaign organization, documentation, and best practices
• Participate in client deliverables and internal meetings, supporting senior team members as needed
• Stay up to date on digital marketing trends, tools, and platform updates

Requirements

• 1-2 years of experience or internship exposure in digital marketing, paid media, or related fields
• Basic familiarity with Google Ads and/or paid social platforms (Meta Ads Manager preferred)
• Strong interest in performance marketing and digital advertising
• Analytical mindset with attention to detail and willingness to learn
• Good communication and organizational skills
• Ability to work collaboratively in a team environment
• Proficiency in Excel/Google Sheets is a plus
• Bachelor’s degree in marketing, communications, or a related field (or equivalent experience)

Nice to Have

• Internship or coursework related to paid media or digital marketing
• Exposure to tools like Google Analytics or other reporting platforms
• Agency or fast-paced work environment experience

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Senior Manufacturing Technology Leader

Location: United States preferred

Travel: Moderate travel as needed

Compensation: Competitive executive compensation package

About the Opportunity

We are partnering with a global manufacturing organization undergoing significant expansion and modernization across its production network. As part of that growth, the company is seeking a senior leader to drive the strategy and execution of its manufacturing technology organization on a global scale.

This is a high-impact executive leadership opportunity for someone who thrives at the intersection of manufacturing, software, data, automation, and enterprise technology. The role will be responsible for shaping and leading the technology roadmap that supports factory performance, automation, scalability, and long-term operational excellence across a large international footprint.

The Role

This leader will oversee global manufacturing technology strategy and execution across a complex manufacturing environment that includes advanced production sites, assembly/test operations, and centralized manufacturing organizations. The role carries broad organizational scope, including responsibility for a large global team and multiple senior leaders/direct reports.

This person will be expected to unify and scale historically siloed teams, align technology priorities with business and operational goals, and build the systems, platforms, and capabilities needed to support the next phase of manufacturing growth.

The right candidate will bring a strong mix of executive leadership, operational rigor, technical depth, and transformation experience. This is not purely an innovation-focused role. It is a strategy-and-execution leadership seat for someone who can define the roadmap and ensure it is delivered effectively across a global organization.

Key Responsibilities

Strategic Leadership

• Define and execute a global manufacturing technology vision and roadmap
• Align technology investments with broader manufacturing growth and operational priorities
• Lead large-scale transformation efforts across manufacturing systems, digital infrastructure, and automation capabilities
• Build a cohesive global operating model across distributed teams and locations
• Balance short-term delivery needs with long-term platform modernization

Manufacturing Technology & Digital Transformation

• Lead modernization of manufacturing technology platforms and factory systems
• Oversee initiatives across manufacturing systems, process control, automation, data infrastructure, and digital operations
• Drive adoption of scalable, future-state architectures that support increasingly automated and data-driven factories
• Partner with operations, engineering, and manufacturing leadership to improve plant performance through technology
• Establish and standardize global solutions rather than localized one-off site approaches

Data, Software, and AI Enablement

• Lead the evolution of enterprise data and analytics capabilities within manufacturing
• Drive adoption of modern data platforms, predictive analytics, and AI/ML use cases in industrial environments
• Enable technology capabilities tied to productivity, throughput, cost optimization, quality improvement, and decision support
• Support modernization of software engineering practices, including agile delivery, DevOps, and scalable platform development
• Help integrate manufacturing systems with broader enterprise technologies and business platforms

Operational Excellence

• Improve factory performance through better use of systems, data, and automation
• Increase speed of deployment for new capabilities across the manufacturing network
• Support efforts tied to uptime, throughput, cost reduction, and scalable automation
• Develop and track performance metrics that tie technology outcomes to operational business results
• Build organizational discipline around execution, prioritization, and continuous improvement

Leadership & Organization Building

• Lead and develop a large, globally distributed team through multiple senior leaders/direct reports
• Build strong leadership bench strength across software, automation, data, and manufacturing technology disciplines
• Foster a culture of collaboration, accountability, innovation, and operational excellence
• Create alignment across business, IT, and manufacturing stakeholders in a highly matrixed environment
• Help scale the organization to support long-term manufacturing expansion

Ideal Candidate Profile

We are looking for an executive leader who has successfully operated in large, complex environments and understands how to use technology to improve manufacturing performance at scale.

The ideal background will include:

• Significant experience leading manufacturing technology, digital manufacturing, smart manufacturing, operational technology, or manufacturing IT functions
• Proven success driving both strategy and execution in large global organizations
• Strong leadership experience managing senior leaders and distributed teams
• Deep understanding of how software, data, cloud, and automation can improve manufacturing operations
• Experience leading complex transformations across multiple sites, regions, or business units
• Strong cross-functional partnership skills with operations, engineering, and enterprise technology stakeholders
• Executive presence with the ability to influence at senior leadership levels

Preferred Technical / Functional Experience

Strong candidates will bring depth in several of the following areas:

• Manufacturing technology platforms
• Manufacturing execution systems and factory systems
• Process control and automation environments
• Operational technology and industrial systems
• Enterprise data platforms and analytics
• AI/ML applications in industrial or manufacturing settings
• Cloud modernization and scalable digital infrastructure
• Modern software engineering and platform delivery models
• Global standardization of systems, processes, and manufacturing technologies

Required Qualifications

• 15+ years of leadership experience in manufacturing technology, industrial technology, factory systems, automation, or related areas
• Experience leading large-scale transformation initiatives in complex enterprise environments
• Demonstrated success managing large, global, cross-functional teams
• Proven track record of delivering measurable operational improvements through technology
• Strong understanding of the intersection of manufacturing, data, software, and automation
• Bachelor’s degree required; advanced degree in engineering, computer science, data science, or related discipline preferred

Preferred Backgrounds

Candidates may come from a range of large-scale manufacturing or industrial environments, including:

• Advanced manufacturing
• Electronics
• Automotive
• Aerospace
• Industrial equipment
• Consumer manufacturing
• Other complex global manufacturing environments

Large-company experience is important. The strongest candidates will have led within highly matrixed organizations where scale, complexity, and cross-functional alignment were critical to success.

Why This Role

This is an opportunity to lead one of the most strategically important functions in a global manufacturing environment undergoing major expansion and transformation. The role offers the chance to shape how technology enables manufacturing performance over the next decade, while building and leading a large organization responsible for execution at scale.

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This person builds and maintains the backend data system that turns raw healthcare data into secure, reliable, and useful insights for better decision-making.

The Company:

This growing start-up has created a ML observability platform that detects AI/ML model issues. They are seeking an experience Senior Solutions Architect to help promote the platform to their clients while also bridging relationships with technical stakeholders.

Core Skill Areas

• Data platform architecture
• Data engineering infrastructure
• System integration’s across tools
• Platform administration and ownership
• Data pipeline ecosystems

YOUR SKILLS AND EXPERIENCE

• 5+ years in Solutions Architecture
• Strong experience building data warehouses/platforms from scratch
• Advanced Snowflake and/or AWS or Azure
• Strong data modelling expertise
• Experience with dbt (preferred)

Healthcare data experience:

• Claims data, EHR/EMR systems
• HL7 / FHIR
• Understanding clinical vs. transactional data

AI exposure:

• Experience integrating AI tools OR
• Strong self-driven projects (LLMs, automation, experimentation)

Benefits:

As a Solutions Architect, you can expect a base salary between $175,000-$200,000+ (based on experience) plus competitive benefits, bonuses, and stock options.

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Overview

We are seeking a Senior Data Modeler to join a growing Enterprise Data & Analytics team. This is a newly created role focused on delivering high-impact analytics that directly support day-to-day business decision-making. The position plays a critical role in shaping dimensional data models, strengthening the data warehouse, and partnering closely with business stakeholders to translate requirements into scalable analytic solutions.

This is a hands-on individual contributor role that blends strong technical expertise with stakeholder engagement and business understanding.

Key Responsibilities

• Partner directly with business and domain stakeholders to gather, analyze, and clarify data and analytics requirements
• Translate business needs into dimensional data models and design artifacts
• Implement enhancements and changes within an existing enterprise data warehouse
• Build and maintain gold-layer data models to support reporting and dashboards
• Collaborate closely with data modeling peers and senior analytics leadership
• Participate in regular meetings across technical and business teams
• Support analytics consumption through well-structured, performant SQL models
• Contribute within an Agile delivery environment

Required Skills & Experience

• Strong experience with dimensional data modeling (Kimball methodology)
• Advanced SQL skills for analytics and data consumption
• Hands-on data warehouse development experience
• Experience implementing and enhancing enterprise-scale data models
• Ability to work directly with business stakeholders and translate needs into technical solutions
• Excellent verbal and written communication skills

Preferred / Nice-to-Have Skills

• Experience with Snowflake
• Experience with data integration tools such as Matillion
• Familiarity with Power BI or similar BI platforms
• Python experience (preferred but not required)
• Experience working in Agile development environments

Ideal Candidate Profile

• Background in data engineering, analytics engineering, or data modeling
• Comfortable being hands-on while collaborating across technical and business teams
• Independent thinker who enjoys solving complex business problems with data
• Highly driven, proactive, and adaptable
• Strong ability to articulate design decisions clearly and confidently

Education

• Bachelor’s degree in Computer Science or a related field (or equivalent professional experience)

Career Growth

This role offers clear growth opportunities over the next 2-3 years, with paths into:

• Deeper specialization as a business domain partner, or
• Broader technical progression toward a senior or architect-level role

Work Environment

• Hybrid work model
• Agile, collaborative team culture
• Opportunity to work across multiple domains and technologies

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Senior Data Scientist

London (Hybrid, 2 days per week) | £75,000 to £95,000 + bonus

This is a chance to take ownership of end-to-end machine learning products within a large-scale personalisation programme, where data science directly shapes customer experiences. You will work on production systems rather than proofs of concept, with clear visibility of impact across a highly engaged user base. The role combines technical depth, leadership, and close collaboration with product and engineering teams.

The Company

They are a well-established UK organisation operating at scale, with data and AI at the heart of their long-term strategy. The business is undergoing a significant AI transformation, embedding intelligence and personalisation into core products rather than treating data science as a support function. With a strong investment in modern platforms and partnerships, they offer a stable yet ambitious environment for senior data scientists.

The Role

• Own the full lifecycle of data science and machine learning products, from problem definition through to deployment and iteration
• Design, build, and maintain production-ready ML systems that drive personalised customer experiences
• Lead a small delivery pod, providing technical direction and mentoring to data scientists
• Translate ambiguous business problems into well-scoped, measurable data science initiatives
• Work closely with data engineering, software engineering, and product teams to ensure solutions are scalable and adopted
• Measure and optimise model performance and real-world impact, including engagement and behavioural outcomes
• Contribute to broader AI adoption and best practices across the organisation, including emerging generative AI use cases

Your Skills and Experience

• Strong commercial experience applying machine learning techniques such as regression and classification to real-world problems
• Advanced Python and SQL skills, with experience working across complex datasets
• Proven track record of delivering production machine learning solutions end to end
• Experience leading data science projects and guiding others through delivery
• Confident communicating with both technical and non-technical stakeholders
• Comfortable working in ambiguous environments and shaping solutions proactively

What They Offer

• Salary between £75,000 and £95,000 depending on experience
• Performance-related bonus paid twice yearly
• Hybrid working with two days per week in a London office
• Comprehensive benefits package including health, pension, and wellbeing support
• Clear opportunity to influence strategy, grow technical leadership skills, and work on high-impact AI initiatives

How to Apply

If this sounds like the perfect role, please apply below!

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Data Engineer

Location: New York Metro (Hybrid)

Pay: $150k – $200k base + bonus

About the Role & Company

This is an opportunity to join a highly technical, growth-focused investment organisation operating at the intersection of technology, data, and capital. The firm invests exclusively in technology and technology-enabled businesses and maintains a flat, meritocratic culture with strong emphasis on collaboration, trust, and engineering judgment.

The organisation is undergoing a significant data and AI transformation, building foundational infrastructure from the ground up to support investment decision-making, portfolio analysis, and automation. This role sits at the centre of that effort and works closely with investment professionals and senior technical leadership.

Responsibilities

• Build and maintain production-grade data pipelines across structured and unstructured data sources
• Organise and structure fragmented internal and external datasets into scalable, reliable systems
• Design and implement data architecture using modern cloud platforms (e.g., AWS, Snowflake)
• Enable downstream analytics and AI-driven workflows through high-quality data foundations
• Independently evaluate and select appropriate tools and technologies
• Support lightweight AI or agent-based workflows embedded within broader systems
• Partner closely with technical leadership and non-technical stakeholders to support real investment use cases
• Ensure data reliability, scalability, and maintainability across systems

Must-Have Qualifications

• 2-4 years of experience in data engineering or analytics engineering
• Strong proficiency in SQL and Python
• Hands-on experience building and maintaining production data pipelines
• Experience working with cloud data platforms Snowflake, AWS
• Solid understanding of data architecture and engineering trade-offs
• Ability to work independently with strong technical judgement

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Your primary focus will be to work with our proprietary and commercial datasets to find critical connections, derive actionable knowledge, and identify potential issues that help our government clients make more informed decisions. Your role will involve designing, developing, and rapidly deploying scalable AI solutions that transform these insights into mission-critical capabilities. You will have the opportunity to expand and grow data-driven research across our organization, leading new areas to apply advanced analytics to drive strategic business and national security results. As part of our team, you must be an AI expert with a strong command of data science fundamentals and a proven ability to bring data-driven solutions to life within the defense ecosystem.

Scope of Responsibilities

*Develop AI/ML/DS systems to address defense problems.

*Develop new AI-based stack of technologies for particular customer needs.

*Development of evaluation solutions for AI deployments.

*Lead the end-to-end execution of AI projects, ensuring alignment with strategic objectives and timely delivery.

*Work closely with partner teams, including AI research, data engineering, and software development, to deliver robust AI systems.

*Collaborate with the AI leadership to clearly define product and applications scope, translating high-level requirements into actionable technical plans and delivering AI platforms and solutions.

*Drive the development of scalable, AI-based platforms designed to support and power solutions for a diverse range of customers within the defense ecosystem.

*Champion the introduction of new AI innovations. Stay current with the rapidly evolving fields of Artificial Intelligence, Large Language Models (LLMs), and agentic systems, and actively transfer this knowledge and best practices for implementation across the team.

*Create agentic AI systems, using AI orchestrators and particular AI reasoning capabilities as tools.

Qualifications

*U.S. Citizenship is required

*Oversee the full lifecycle of AI projects within our AI ecosystem.

*Understanding of coding AI (such as Claude Code) and experience how to use it to scale up AI team deliveries

*Collaborate with cross-functional teams (AI Research, Data Engineering, Software Development).

*Define robust software architecture for AI systems and project roadmaps.

*Translate high-level AI system requirements into actionable technical plans.

*Deliver production-ready AI solutions integrated with clients data platforms and workflows.

*Drive the implementation of scalable AI/ML platforms.

*Maintain deep expertise in cutting-edge AI, including LLMs and agentic systems. Train models, build systems based on AI innovations

*Demonstrate strong National Security domain knowledge.

Desired Skills

*A strong publication record in the top conferences in one of the AI, ML NLP, decision science areas

*Deep knowledge of LLM and Agentic system evaluation, experience in building evaluation systems

*Experience in LLM posttraining or fine tuning

*Experience with MLOps practices, including deployment, monitoring, and management of large-scale models in cloud environments (e.g., GCP, AWS, Azure).

*Track record of successfully transitioning AI research prototypes into robust, production-grade enterprise solutions

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Data Engineer

up to £90,000 + Benefits
London (Hybrid)
This is a great opportunity to join a high‑growth adtech scale‑up where you can take ownership of large‑scale data infrastructure that directly powers machine learning, product intelligence, and customer ROI.

THE COMPANY

This is a UK‑based adtech SaaS platform that using machine learning and real‑time behavioural analytics to help brands optimise performance.

THE ROLE

Key responsibilities include:

• Designing, building, and maintaining batch and streaming data ingestion pipelines for high‑volume event data
• Improving and optimising the AWS Redshift data warehouse, including modelling, performance, and cost efficiency
• Refactoring poorly structured data into clean, well‑governed, ML‑friendly datasets
• Building pipelines to support ML workflows, feature stores, A/B testing, and experimentation
• Ingesting and integrating new and under‑utilised data sources
• Working on greenfield projects while scaling existing data infrastructure to billions of data points

YOUR SKILLS AND EXPERIENCE

You will bring strong capability in:

• Python and SQL
• AWS data infrastructure (S3, Redshift, Glue, Athena, Kinesis, Lambda)
• End‑to‑end ownership, from proof‑of‑concept through to production

THE BENEFITS

You will receive a salary of up to £90,000 depending on experience, along with a comprehensive benefits.

HOW TO APPLY
Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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