SLSQ427R253

As a Partner Solutions Architect for Europe, you will work with the technical and sales team members who work directly with our customers. You will develop 'technical champions’ within our top Partners, providing enablement on technical matters related to the Databricks product. Working with our partners, you will help our customers achieve tangible, data-driven outcomes through our Databricks Data Intelligence Platform, enabling data teams to complete projects and integrate them into their enterprise Ecosystem. As a member of our team, you will exercise and develop expertise in those areas, using open source projects such as Apache Spark™, MLflow, and Delta Lake, and major public cloud infrastructure and services. the product. You will use this expertise to become a trusted advisor to C&SI partners.

The impact you will have:

• Provide partners with the level of enablement they need to assist their clients in evaluating and adopting Databricks, including hands-on Apache Spark™ programming and integration with the wider cloud ecosystem.

• Engage with the partner technical community by leading workshops, seminars, and meet-ups.

• You will be a big data analytics expert in architecture and design, and will share this knowledge with our partner network.

• Show expertise by producing creative technical solutions and blog posts.

What we look for:

• 8 years of customer-facing experience working with external clients or partners across a variety of industry markets

• Core strength in either data engineering or data science

• Experience demonstrating technical concepts, including presenting and whiteboarding

• Experience developing architectures within a public cloud (AWS, Azure, or GCP)

• Hands-on experience in SQL, Python, Scala, or Java

• Expertise in at least one of the following:

• Data Engineering technologies (Ex, Apache Spark™, Hadoop, Kafka)

• Data Warehousing (Ex, SQL, OLTP/OLAP/DSS)

• Data Science and Machine Learning technologies (Ex, pandas, scikit-learn, HPO)

The role

We seek an experienced Specialist Solutions Architect to support AI-focused customers leveraging Nebius services. In this role, you will be a trusted advisor, collaborating with clients to design scalable AI solutions, resolve technical challenges and manage large-scale AI deployments involving hundreds to thousands of GPUs.

You’re welcome to work on-site in Amsterdam or remotely from any other EU country.

Your responsibilities will include:

• Designing customer-centric solutions that maximize business value and align with strategic goals.
• Building and maintaining long-term relationships to foster trust and ensure customer satisfaction.
• Delivering technical presentations, producing whitepapers, creating manuals and hosting webinars for audiences with varying technical expertise.
• Collaborating with engineering and product teams to effectively prioritize and relay customer feedback.

We expect you to have:

• 3+ years of experience with cloud technologies in MLOps engineering, Machine Learning engineering or similar roles.
• Strong understanding of ML ecosystems, including models, use cases and tooling.
• Proven experience in setting up and optimizing distributed training pipelines across multi-node and multi-GPU environments.
• Hands-on knowledge of frameworks like PyTorch or JAX.
• Excellent verbal and written communication skills.

It will be an added bonus if you have:

• Expertise in deploying inference infrastructure for production workloads.
• Ability to transition ML pipelines from POC to scalable production systems.

Preferred tooling:

• Programming Languages – Python, Go, Java, C++
• Orchestration – Kubernetes (K8s), Slurm
• DevOps Tools – Git, Docker, Helm
• Infrastructure as Code (IaC) – Terraform
• ML Frameworks and Libraries – PyTorch, TensorFlow, JAX, HuggingFace, Scikit-learn

We are looking for a Senior Data Scientist to join our Product Engineering team in Helsinki, Dublin, or the UK. 

If you are a naturally curious problem-solver who thrives on discovering innovative ways to extract value from data, this is your chance to lead high-impact initiatives for a fast-growing SaaS powerhouse

In this role, you will… 

• Solving the "Unsolvable": Dive into massive datasets to architect and implement robust, data-driven solutions that solve high-stakes business problems for our customers.
• Product-Embedded Innovation: Focus on building and embedding insights directly into the Supermetrics product suite, moving beyond theory into live, functional features.
• The Scale-Up Mindset: Thrive in a high-velocity environment where you are expected to pioneer new solutions, remain creative, and lead with a relentless "product-first" focus.
• Fueling the AI Engine: Leverage Supermetrics’ one-of-a-kind dataset to build market-differentiated products. If data is the fuel for AI, you’ll be sitting on one of the best "refineries" in the industry.
• High-Leverage Impact: Utilize our unique data access to create solutions that simply can’t be built anywhere else, giving you the platform to make a massive, visible impact on the industry

Your day-to-day work and responsibilities include…

• Identify opportunities to use advanced data science techniques leveraging a wide variety of MarTech data to solve problems and provide new insights to our customers.
• Develop and deploy AI/ML solutions, creating new products and value for our customers.
• Transform data science prototypes into scalable, production-ready, data-driven products in partnership with our infrastructure/engineering teams.
• Embed AI-powered features and automation tools in data science applications to improve velocity, product quality and customer experience as needed.
• Communicate the impact and outcomes of data science initiatives to stakeholders across the organization.
• Stay current with AI/ML advancements and continually seek for new ideas or paradigms that will add value to our customers.

This position is for you if you have…

• An advanced degree in a STEM-related field such as Mathematics, Statistics, Computer Science, Engineering, or a related field, or equivalent work experience.
• 5+ years of experience in Data Science or ML and AI with real-world data within a product development and/or research setting.
• Expertise in statistical analysis, ML modeling, experimentation, and optimization.
• Hands-on experience working with LLMs and AI agents, including fine-tuning, retrieval-augmented generation (RAG), and deploying models to enhance product features.
• A proactive mindset, a continual pursuit of new ideas and data sources, and the ability to systematically tackle ambiguous problems with a data-driven, hypothesis-based approach.
• Proficiency in Python and SQL, with experience using libraries such as Pandas, NumPy, Scikit-learn, and deep learning frameworks like TensorFlow or PyTorch.
• Experience working with Agent frameworks (e.g. google adk, LangChain) and AI agent evaluation
• Expert-level experience building and deploying data science products using cloud platforms (e.g., AWS, GCP) and MLOps tools.
• Strong project management experience and ability to work with a diverse, distributed, and talented group of people.
• Excellent written and verbal communication skills to explain technical concepts to non-technical stakeholders.
• Domain knowledge of large-scale, data-driven SaaS applications.

We also appreciate…

• Experience with MarTech advanced analytics techniques and use cases (i.e. propensity modelling, Media Mix Modelling, personalisation/customer segmentation).
• Experience in the end-to-end development of AI products.

Benefits we offer…

• Competitive compensation package, including equity
• Great work equipment, and home office allowance for those working in our fully remote locations
• Health care benefit and leisure time insurance
• Annual 1000 euros of personal learning budget
• Sports and wellbeing allowance

Benefits may vary depending on location. 

Hear why our team likes it here at supermetrics.com/careers/life-at-supermetrics.

Get to know our Engineering team at supermetrics.com/careers/engineering

#LI-Remote / #LI-Hybrid #LI-FullTime

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our Berlin office or full remote from any part of Germany.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
  • Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
  • Collaborate with research teams on innovative machine learning experiments
  • Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring
    
    
• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our London office or full remote from any part of the UK.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

As a Staff Machine Learning Engineer in our Applied ML & Research team, you'll drive the development of cutting-edge machine learning solutions that power critical features across our online gaming platforms. Your work will directly impact platform security, user experience, and large-scale data-driven decision-making for hundreds of thousands of users daily.

This role blends hands-on technical work with strategic thinking. You’ll lead by example, contribute high-quality code, and help shape the ML roadmap in the organization through cross-functional collaboration.

What you’ll you be doing:

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives.
• Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems.
• Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment.
• Translate complex technical concepts into clear insights for both technical and non-technical stakeholders.
• Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals.
• Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

We're looking for someone with:

• Master’s degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field.
• 7+ years of industry experience building and deploying ML models at scale.
• Proven ability to lead cross-functional technical initiatives and influence engineering strategy.
• Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL.
• Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar.
• Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies.
• A track record of shipping production-level ML products and maintaining high code quality.
• Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.

Bonus points for:

• Familiarity with ML tooling such as MLflow, ZenML, or Metaflow.
• Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito).
• Exposure to streaming data platforms like Kafka.
• Contributions to open-source ML projects or publications in ML conferences.

AI Engineer - FDE (Forward Deployed Engineer) (ALL LEVELS)

Req ID: CSQ426R186

Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specialisations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap 

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

1211 - Director, Data Science - DTA

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Role Summary and Impact

The Data Science Director, plays a critical leadership role as part of a broader team in the deployment and development of predictive models for our customers. You will lead and mentor a team, working collaboratively with senior Google Cloud and Google Marketing experts to apply advanced modeling techniques to enhance our customers' media/marketing solutions. As Team Lead you will be responsible for guiding the team in building out industry-relevant predictive models that can be applied to optimize our customers' media investments.

The role focuses on leading the application of analytical solutions based on machine learning & statistical predictive algorithms on top of the Google technology stack and agent development for our customers. We are looking for a Team Lead with significant experience in algorithmic data analysis, proven scientific research skills, and a track record of leading successful data science initiatives.

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

This is an excellent opportunity for a Team Lead, to join the Data and Technology Consulting Team. You will be instrumental in strategising how to tackle and take apart large and messy datasets of structured and unstructured data, oversee the building and implementation of models and algorithms, agents and design and run experiments to optimise clients customer insights, analytics and customer experience. The ideal candidate will have a love of getting their hands dirty, while also empowering and developing their team to do the same.

RESPONSIBILITIES:

• Lead the team in the creation, management, and continuous improvement of AI/ML and models and agents used to measure, optimize, and activate business transformation, including creative, media campaigns and broader marketing objectives.
• Drive the development and deployment of industry-relevant strategies and solutions.
• Ensure comprehensive documentation of data science projects, establishing best practices for replicable and scalable analytical processes across clients.
• Guide the team in building out compelling content for presentations to demonstrate the performance and value of statistical and predictive models.
• Oversee the delivery of robust mathematical analysis, ensuring accuracy and strategic relevance.
• Accountable for the team's production of high-standard campaign reports, studies, presentations, and proposals.
• Achieve continuous improvement by proactively assessing Choreograph's working relationships, practices, and methods, and implementing enhancements.
• Lead the establishment and optimization of MLOps processes leveraging the GCP toolset.
• Drive and demonstrate measurable success and impact for clients and the team.

REQUIREMENTS:

• Hands-on experience with building out machine learning models with Python, in a leadership or senior mentorship role.
• Advanced education and background in machine learning, computer science, physics, applied mathematics, or statistics.
• Expert-level hands-on experience in developing complex query structures with SQL and/or NoSQL query languages, and experience guiding others.
• Expert-level hands-on experience working with GCP’s AI Capabilities, including leveraging BigQuery ML, Vertex AI, and other relevant services.
• Extensive hands-on experience with a broad range of machine learning techniques using (TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, Pandas, NLTK, Spark MLib).
• Deep experience and understanding of deep learning techniques (TensorFlow, Theano, MXNet).
• Proven understanding and experience in software engineering best practices, DevOps, and MLOps, with a track record of implementing or leading these initiatives.
• Solid grounding in applied mathematics, especially optimization and graph theory, and advanced statistics.
• Significant commercial or academic experience in leading the development and deployment of complex ML & AI solutions using Python/R.
• In-depth knowledge of machine learning algorithms and their practical applications.
• Advantageous to have extensive experience in Google Marketing Platform and the use of Ads Data Hub.
• Exceptional capabilities in the areas of data engineering, data modeling, and complex big data analysis, with experience leading teams in these domains.
• Strong business analysis skills and deep understanding of analytics, with the ability to translate complex data into strategic business value.
• Exceptional communication and presentation skills, capable of influencing stakeholders at all levels.
• Passionate about working in an extremely fast-paced, demanding, and fluid environment, with a desire to build and lead a high-performing team and contribute significantly to a growing company.

Life at WPP Media & Benefits

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.  

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide.

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