The Data Support Developer is responsible for the day-to-day data support of the Sky Road Product Suite.  They will be responsible for front-line (Tier-1) support of all Sky Road clients and processes during European trading hours, Tier-1 and Tier-2 support of client data questions and issues, and developing scripts and tools to facilitate monitoring, alerting, and reconciliation of client data and processes.  The client support team is the front line of support to all Sky Road clients.  The Data Support Developer will communicate with the development team on support issues that require escalation.  They will also work with the project management team to assist with the onboarding of new clients and to understand new client workflows to facilitate support.  The Data Support Developer will also assist with the QA testing process of data workflows during client onboarding and releases.

The Sky Road technology team consists of front-end developers, server-side developers, and data developers. The technology teams closely collaborate with each other, the client services team, and senior management to deliver the latest features into the Sky Road products. This role will ensure the client’s experience is a success.

Key Responsibilities

• Tier-1 support for Sky Road clients during European Trading hours.
• Tier-1 and Tier-2 support for Sky Road client data issues and inquiries.
• Develop scripts and tools to monitor, alert, and reconcile client data and processes.
• Monitor and troubleshoot inbound and outbound data flows.
• Monitor scheduling software, error queues and email for potential support issues.
• Communicate and escalate with the development team on support issues.
• Coordinate with project managers on client onboarding.

Required Qualifications

• Python 3.x experience, at least 2 years.
• Experience with Python packages: Pandas, Numpy, botos, and sqlalchemy.
• Experience with Relational/NoSQL Databases.
• Experience working in a support capacity.
• Strong Excell skills. Must possess the ability to join, pivot and summarize data.
• Ability to troubleshoot support issues.
• Attention to details.
• Experience working in a team environment.

Desired Qualifications

• Understanding of Order Management, Portfolio Management, Compliance and Security Master systems.
• Understanding of core financial data domains including issuers, instruments, industries, ratings, and pricing of financial products.
• Experience with scheduling software.
• Experience with software product support.
• Experience with server-side API frameworks such as REST.

Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development team. Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models. 

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.

Profile

• You’re excited to apply your research expertise to identify new opportunities in worldwide markets  
• You enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently
• You are a critical thinker who can learn and implement new skills in a fast-changing environment

Qualifications

• You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2026
• Fluency in Python
• Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
• Brilliant analytical and problem-solving skills
• Ability to work creatively and independently on long-term technical problems

The estimated base salary for this position is 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed!

Responsibilities 

• Analyze time series network and exchange protocol captures
• Become familiar with the details of specific markets, attend presentations and liaise with exchange counterparts
• Research exchange features, capabilities, and architecture
• Automate collection and visualization of metrics that quantify efficacy of exchange communication
• Formulate and conduct controlled experiments that measure impact of calculated changes to HRT’s trading infrastructure
• Communicate ideas, requirements, and results across disparate teams
• Improve fill rate of our hardware-based trading strategy
• Reduce incidence of cancel-reject responses
• Investigate and report details of various latency-sensitive exchanges

Profile 

• You possess a degree in Data Analytics or a related field
• You can collect and interpret network and/or financial market data
• You have professional experience in latency reduction, preferably in finance
• You have a basic understanding of proprietary trading and exchange technologies

Skills 

• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Basic understanding of TCP and UDP network protocols
• Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy)
• Some familiarity with the details of modern computer systems and networks
• Experience with real time exchange market data and order entry a plus

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

We seek a quantitative researcher to join our Investment Management & Research group. As part of a collaborative quant team, you will partner with portfolio managers, researchers and technologists to implement and operate our core systematic macro strategies.

Your responsibilities will include:

• Researching and backtesting systematic macro trading signals
• Developing and operating trading strategies across a wide range of markets
• Partnering with data engineering and technology teams to build and improve infrastructure

What we are looking for:

• Previous experience (2+ years) working in a systematic macro trading environment, preferably as part of an established quant group trading futures, forwards and related markets
• Data analysis and coding experience (preferably Python/pandas/numpy)
• Strong communication skills with the motivation to work in a large collaborative investment group structure

Note: We are currently recruiting for multiple levels and positions, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.
• Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.
• Own Research work-streams at different levels, depending on seniority.
• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
• Collaborate with colleagues beyond the research team to translate your models into production-ready code.
• Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.
• Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.
• Ability to scope and effectively deliver projects.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following:
  1. operator learning (neural operators), or other probabilistic methods for PDEs;
  2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;
  3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).
• >2 years of experience in a data-driven role in a professional industry setting (excluding post-doc positions), with exposure to:
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  • developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);
  • iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;
  • combining theoretical reasoning with empirical intuition to guide investigation;
  • formulating and running experiment pipelines to benchmark models and produce comparable results;
  • writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.
• Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

1429 - Associate Director, Analytics - DAT

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 EssenceMediacom: A Leading WPP Media Brand

EssenceMediacom is a new breed of media agency. Grounded in analytics & insights and powered by data & technology, we believe in the power of media and creative to drive breakthroughs for the world’s best brands. We help clients understand the modern marketing paradox and discover the breakthroughs brands need to win with their consumers. We are designed for the new communications economy — built on data & technology, built for people & algorithms, built around diverse schools of thought, built to test & learn at scale, and, crucially, built to evolve.

Role Summary and Impact

We are seeking an Associate Director to join our growing Analytics & Insights team, reporting into the Analytics Director. The team focuses on media effectiveness measurement, campaign analysis and client communication to help make brands become more valuable to the world.

You will be working with leading advertisers, including Airbnb, to harness their data and improve the performance of their campaigns, developing and deploying media measurement solutions. Communication with client stakeholders and effective management of assigned tasks is critical in this role. You will be joining an award winning team, with more than 16 tech and media industry awards to our name, including Campaign Magazine’s Tech Awards Agency of the Year, Best Use of AI, and Breakthrough Tech as Part of a Campaign awards.

We have invested in giving you the tools to make you as successful as possible, including training/development, full access to Google Cloud Platform and a wider global community of analysts and data scientists.

Some of the things we'd like you to do

• Build and apply a deep understanding of marketing objectives to support Account teams with comprehensive measurement and testing plans.
• To help deliver “best in class” analytical capabilities across the agency with the wider Analytics team, including the use of new methods, techniques, tools and systems. Managing the process through to delivery and taking ownership of global roll out. 
• Recruit, manage, and develop a team of 1-3 analysts, ensuring high-quality output and efficient workflow.
• Lead the creation of clear, robust and thought-provoking campaign reviews and insights, and show the wider team/clients how to improve effectiveness. 
• Develop deep understanding of marketing platform testing and targeting abilities, and act in a consultative capacity in their implementation
• Deliver insightful campaign reviews with actionable recommendations to improve marketing effectiveness.
• Provide actionable insights and design experiments to optimise campaign performance - focusing on brand and conversion lift studies.
• Be a reliable day-to-day point of contact for clients and maintain robust client relationships.
• Coordinate with third-party vendors for the assessment and management of bespoke measurement solutions, including contracts and SOWs.
• Manage relationships with data engineering teams and set automation strategies to integrate new tools and solutions.
• Translate complex data concepts for stakeholders and contribute to the company's data strategy, promoting data-driven innovation within the media industry.

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.

• You will be highly numerate: able to confidently interpret data and apply statistical tests to draw robust conclusions. Holding a degree(s) in a quantitative field: Statistics, Mathematics, Economics, Engineering, Physical Science or Computer Science
• Experience in analytics, measurement, data science, or a related field
• Knowledge of applying measurement to media campaigns through Meta/Google, through brand and conversion lift studies, matched market tests or otherwise
• Well developed problem-solving skills and the ability to think critically and creatively
• Strong understanding of statistics including hypothesis testing, descriptive statistics and distribution theory
• Strong communication skills, with the ability to present complex ideas to both technical and non-technical audiences
• Able to work independently and as part of a cross-functional team, using project management tools such as Jira/Trello. Ability to project manage analytics projects.
• Highly capable at presenting data in a visually engaging and insightful manner that cuts through the noise
• Experience in mentorship and management, ability to display empathy in difficult situations and lead by example
• Stay up-to-date with the latest industry trends and advancements in data science and analytics
• Proficiency in SQL & R/Python, including understanding of packages such as pandas, numpy, scipy & matplotlib. 
• Strong understanding of what data points can be collected and analysed in a digital campaign, and how each data point should be analysed. Including knowledge of media data and incremental measurement, including both Direct Response and Brand campaigns

Nice to haves:

• Experience with digital ad technologies (SA360, GA, Campaign Manager, DV360, Meta Business Manager), site analytics and tools
• Experience with cloud technologies, such as GCP
• Proven understanding and experience with digital ad platforms APIs
• Knowledge of market research methodologies
• Speaking any European languages

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.

#LI-Promoted

Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
• Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
• Transform prototype model implementations to robust and optimised implementations.
• Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
• Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
• Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
• Own Research work-streams at different levels, depending on seniority.
• Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
• Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
• Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
• Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
  
  • Scientific computing;
  • High-performance computing (CPU / GPU clusters);
  • Parallelised / distributed training for large / foundation models.
• Ideally >2 years of experience in a data-driven role in a professional setting, with exposure to:
  • scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
  • distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
  • cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);
  • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
  • C/C++ for computer vision, geometry processing, or scientific computing;
  • software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);
  • container-ization and orchestration (Docker, Kubernetes, Slurm);
  • writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

Note: We are currently recruiting for multiple positions across different levels, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Shape Research group strategy and culture in a significant way, especially in domains of expertise.
  • Be opinionated and formulate strategy on engineering topics relevant to our Research priorities, especially on: scaled engineering, securing compute, infrastructure stack.
  • Define necessary profiles to execute this strategy.
  • Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.
  • Nurture younger colleagues to grow their skillset and guide their professional development.
• Own Research work-streams at a high-level to deliver outcomes.
  • Align priorities with problem stakeholders, internal and external.
  • Set the technical direction for the stream and apply judgement and taste to drive progress.
  • Plan roadmaps with clear milestones for key decisions and outcomes.
  • Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.
  • Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.
• The below activities in particular.
  • Work closely with our research scientists and simulation engineers to build and deliver models that address real-world physics and engineering problems.
  • Design, build and optimise machine learning models with a focus on scalability and efficiency in our application domain.
  • Transform prototype model implementations to robust and optimised implementations.
  • Implement distributed training architectures (e.g., data parallelism, parameter server, etc.) for multi-node/multi-GPU training and explore federated learning capacity using cloud (e.g., AWS, Azure, GCP) and on-premise services.
    • Work with research scientists to design, build and scale foundation models for science and engineering; helping to scale and optimise model training to large data and multi-GPU cloud compute.
  • Identify the best libraries, frameworks and tools for our modelling efforts to set us up for success.
  • Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
  • Work at the intersection of data science and software engineering to translate the results of our Research into re-usable libraries, tooling and products.
  • Foster a nurturing environment for colleagues with less experience in ML / Engineering for them to grow and you to mentor.

What you bring to the table

• Enthusiasm about developing machine learning solutions, especially deep learning and/or probabilistic methods, and associated supporting software solutions for science and engineering.
• Ability to work autonomously and scope and effectively deliver projects across a variety of domains.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• MSc or PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, software engineering, or a related field, with a record of experience in any of the following:
  • scientific computing;
  • high-performance computing (CPU / GPU clusters);
  • parallelised / distributed training for large / foundation models.
•  4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in most of the below:
  • • scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus);
    • employing distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton);
    • employing cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP);
    • building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications;
    • building or using C/C++ for computer vision, geometry processing, or scientific computing;
    • following and promoting software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps);
    • container-izing and orchestrating compute tasks (Docker, Kubernetes, Slurm);
    • writing pipelines and experiment environments, including running experiments in pipelines in a systematic way.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

Note: We are currently recruiting for multiple levels and positions, however please only apply for the role that best aligns with your skillset and career goals.

What you will do 

• Own Research work-streams at a high-level to deliver outcomes.
  • Align priorities with problem stakeholders, internal and external.
  • Set the technical direction for the stream and apply judgement and taste to drive progress.
  • Plan roadmaps with clear milestones for key decisions and outcomes.
  • Organise and guide the more junior members of the team to effectively execute and deliver against this roadmap.
  • Communicate purpose and key outcomes to raise awareness across the company and create opportunities for use and deployment.
• Contribute towards Research group strategy and culture.
  • Identify research areas that would be valuable to the company and champion their development, ordering wrt other research objectives.
  • Promote effective working patterns and proactively flag issues with team dynamics to foster a productive environment.
  • Nurture younger colleagues to grow their skillset and guide their professional development.
• The below activities in particular.
  • Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations.
  • Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques.
  • Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems.
  • Collaborate with colleagues beyond the research team to translate your models into production-ready code.
  • Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences.

What you bring to the table

• Ability to scope and effectively deliver projects.
• Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering.
• Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills — with teams and customers alike.
• PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following:
  1. operator learning (neural operators), or other probabilistic methods for PDEs;
  2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data;
  3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.).
• Ideally, >4 years of experience in a data-driven role in a professional industry setting, where you have been instrumental in:
  • building machine learning models and pipelines in Python, using common libraries and frameworks (PyTorch / CUDA, ideally with exposure to JAX, NumPy / SciPy), especially including deep learning applications;
  • developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical);
  • iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance;
  • combining theoretical reasoning with empirical intuition to guide investigation;
  • formulating and running experiment pipelines to benchmark models and produce comparable results;
  • writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience.
• Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR.

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

🏦 10% employer pension contribution - because investing in future matters.

🍽️ Free office lunches - to keep you energised and focused.

👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

🍼 YellowNest nursery scheme - to help working parents manage childcare costs.

☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.

💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.

👀 Eye tests - because good work depends on good health.

📈 Personal development - dedicated support for learning, development, and leveling up over time.

💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.

🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.

🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

🔎 Watch this space, we’re continuing to build this as we grow…

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

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

1721 - Associate Director, Analytics

WPP is the trusted growth partner for the world's leading brands. With exceptional talent, trusted data and intelligence, and world-class partnerships - all united by our pioneering agentic marketing platform, WPP Open - we help clients navigate change, capture opportunity, and deliver transformational growth.

WPP Media is WPP's AI-driven media operating unit, bringing together media, data, and partnerships to deliver creative personalisation at scale. Connected through WPP Open and powered by Open Intelligence, clients see exactly where, how, and why their media investment is working.

For more information, visit wppmedia.com.

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 EssenceMediacom: A Leading WPP Media Brand

EssenceMediacom is a new breed of media agency. Grounded in analytics & insights and powered by data & technology, we believe in the power of media and creative to drive breakthroughs for the world's best brands. We help clients understand the modern marketing paradox and discover the breakthroughs brands need to win with their consumers. We are designed for the new communications economy - built on data & technology, built for people & algorithms, built around diverse schools of thought, built to test & learn at scale, and, crucially, built to evolve.

Role Summary and Impact

We are seeking an Associate Director to join our Global Analytics & Insights team, reporting into the VP of Global Analytics. The team focuses on media effectiveness measurement, campaign analysis and client communication to help make brands become more valuable to the world.

You will be working with a leading travel brand, to harness their data and improve the performance of their campaigns, developing and deploying media measurement solutions. Communication with client stakeholders and effective management of assigned tasks is critical in this role. You will be joining an award winning team, with more than 16 tech and media industry awards to our name, including Campaign Magazine's Tech Awards Agency of the Year, Best Use of AI, and Breakthrough Tech as Part of a Campaign awards.

We have invested in giving you the tools to make you as successful as possible, including training/development, full access to Google Cloud Platform, an integrated AI platform leveraging common marketplace LLMs as well as access to a wider global community of analysts and data scientists.

Some of the things we'd like you to do

Partner with the Global Analytics lead to develop and communicate global measurement frameworks to local regional and market level teams

Operationalize global measurement approaches such local regions and markets approach media analytics in a consistent way

Develop standardized analytics tools and analysis through the development of AI agents

Build and apply a deep understanding of marketing objectives to support Account teams with comprehensive measurement and testing plans.

Develop deep understanding of marketing platform testing and targeting abilities, and act in a consultative capacity in their implementation to regional teams

Deliver insightful campaign reviews with actionable recommendations to improve marketing effectiveness.

Provide actionable insights and design experiments to optimise campaign performance - focusing on brand and conversion lift studies.

Be a reliable day-to-day point of contact for global clients and maintain robust client relationships.

Coordinate with third-party vendors for the assessment and management of bespoke measurement solutions, including contracts and SOWs.

Manage relationships with data engineering teams and set automation strategies to integrate new tools and solutions.

Translate complex data concepts for stakeholders and contribute to the company's data strategy, promoting data-driven innovation within the media industry.

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.

• You will be highly numerate: able to confidently interpret data and apply statistical tests to draw robust conclusions. Holding a degree(s) in a quantitative field: Statistics, Mathematics, Economics, Engineering, Physical Science or Computer Science
• Experience in analytics, measurement, data science, or a related field
• Knowledge of applying measurement to media campaigns through Meta/Google/TikTok/Snapchat/Pinterest, through brand and conversion lift studies, matched market tests or otherwise
• Well developed problem-solving skills and the ability to think critically and creatively
• Strong understanding of statistics including hypothesis testing, descriptive statistics and distribution theory
• Strong communication skills, with the ability to present complex ideas to both technical and non-technical audiences
• Able to work independently and as part of a cross-functional team, using project management tools such as Asana/Wrike. Ability to project manage analytics projects.
• Highly capable at presenting data in a visually engaging and insightful manner that cuts through the noise
• Experience in mentorship and management, ability to display empathy in difficult situations and lead by example
• Stay up-to-date with the latest industry trends and advancements in data science and analytics
• Proficiency in SQL & R/Python, including understanding of packages such as pandas, numpy, scipy & matplotlib is desired
• Strong understanding of what data points can be collected and analysed in across media analytics campaigns, and how each data point should be analysed. Including knowledge of media data and incremental measurement, including both Direct Response and Brand campaigns

Nice to haves:

• Experience with digital ad technologies (SA360, GA, Campaign Manager, DV360, Meta Business Manager), site analytics and tools
• Experience with cloud technologies, such as GCP
• Proven understanding and experience with digital ad platforms APIs
• Knowledge of market research methodologies
• Speaking any European languages

Life at WPP Media & Benefits

Our passion for shaping the next era of media is powered by our commitment to Be Extraordinary, investing in our employees to inspire transformational creativity. We also Lead Optimistically, firmly believing in and Championing Growth and Development for every individual. This commitment allows WPP Media employees to leverage the extensive global WPP Media & WPP networks to pursue their passions, build vital professional connections, and learn at the cutting edge of marketing and advertising. 

We Create an Open environment built on trust and respect, where everyone feels they belong and has opportunities to progress. This inclusive culture is fostered through a variety of employee resource groups and frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our comprehensive benefits package reflects this commitment, including 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 characteristics. We believe the best work happens when we're together, fostering creativity, collaboration, and connection in this open and supportive environment. 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.

While we appreciate all applications received, only those candidates selected for an interview will be contacted. 

#LI-Promoted

Company Overview

Soros Fund Management LLC (SFM) is a global asset manager and family office founded by George Soros in 1970. With $28 billion in assets under management (AUM), SFM serves as the principal asset manager for the Open Society Foundations, one of the world’s largest charitable foundations dedicated to advancing justice, human rights, and democracy.

Distinct from other investment platforms, SFM thrives on agility, acting decisively when conviction is high and exercising patience when it’s not. With permanent capital, a select group of major clients, and an unconstrained mandate, we invest opportunistically with a long-term view in a wide range of strategies and asset classes, including public and private equity and credit, fixed income, foreign exchange, and alternative assets. Our teams operate with autonomy, while cross-team collaboration strengthens our conviction and empowers us to capitalize on market dislocations.

At SFM, we foster an ownership mindset, encouraging professionals to challenge the status quo, innovate, and take initiative. We prioritize development, enabling team members to push beyond their roles, voice bold ideas, and contribute to our long-term success. This culture of continuous growth and constructive debate fuels innovation and drives efficiencies.

Our impact is measured by both the returns we generate and the values we uphold, from environmental stewardship to social responsibility. Operating as a unified team across geographies and mandates, we remain committed to our mission, ensuring a meaningful, lasting impact.

Headquartered in New York City with offices in Greenwich, Garden City, London, and Dublin, SFM employs 200 professionals.

Job Overview

We are seeking a talented Quantitative Developer to join our team. You will work with the business as an individual contributor to deliver key projects with far-reaching impact on trading, alpha generation, risk management and more. You have Excellent problem-solving skills and the ability to collaborate with cross-functional teams. 

If you value a balanced approach that combines thoughtful innovation with high-quality execution, this opportunity offers the chance to play a key role in strengthening our infrastructure while contributing to our broader mission. 

Major Responsibilities

• Development of real time P&L and risk systems 

• Design systems for quantitative risk and pricing calculations, such as scenario reporting and margin replication  

• Build interactive tools for our portfolio management and risk teams 

• Work with analysts on implementing trading signals across a wide range of asset classes 

• Communicate complex technical concepts effectively to technical and non-technical stakeholders. 
• Support PNL and Risk infrastructure during London hours.

Requirements

• 5+ years of experience in a front office focused quantitative development role 

• Advanced degree in Computer Science, Mathematical Finance, Physics, Engineering, or a related field. 

• Strong proficiency in Python and standard libraries (Pandas, NumPy. Etc.) 

• Exposure to other programming languages (C#, R, etc) 

• Proficiency with SQL 

• Ability to work with business users to create technical specifications for projects 

We anticipate the base salary of this role to be between 150,000-200,000 GBP. In addition to a base salary, the successful candidate will also be eligible to receive a discretionary year-end bonus. 

In all respects, candidates need to reflect the following SFM core values:

Smart risk-taking   //   Owner’s Mindset   //   Teamwork   //   Humility   //   Integrity