11 Data Science jobs in County Dublin

Company Description

TOMRA Food is a multinational organisation and a leading provider of sensor-based sorting, peeling and integrated post-harvest solution for the food industries. Transforming global food production to maximise food safety and minimise food loss by making sure Every Resource Counts, has been our strength for over 50 years.

At TOMRA, we want people to innovate, show passion in their work and be responsible. We encourage the freedom to innovate and take risks that result in breakthroughs that challenge the status quo. We value passion that focuses and commits to meeting success. We believe in a responsible and safe mindset that takes care of our customers, products, and fellow employees.

Join the resource revolution

Job Description

We are looking for a Data Science Architect to lead the design and evolution of our data science systems across machine and cloud platforms. As a key member of the R&D team, you will shape the architecture that powers deep learning inference on TOMRA Food sorters and drive innovation in our cloud-based MLOps platform that was developed to train the models. This role blends technical leadership, system design, and strategic foresight to deliver scalable, high-performance solutions that create real customer value.

Role and Responsibilities:

System Architecture & MLOps:

• Design DL vision models by selecting a suitable backbone, neck and head and testing the performance of those combinations. Innovations in these areas are highly welcomed.
• Design architecture for real-time deep learning inference on TOMRA sorters, including GPU specifications.
• Maintain & improve architecture of in-house cloud-based MLOps platform (data science pipelines).
• Design & advise on new features for the MLOps platform.
• Follow latest improvements in AzureML ecosystem and come up with efficiency improvements.
• Optimise model lifecycle process and come up with performance improvements for our DL models in order to create customer value.
• Produce architectural plans for our data science solutions and ensure that these are well communicated and understood by the rest of the data science team.

Technical Leadership:

• Provide technical leadership and guidance to data scientists.
• Stay up to date of industry trends and emerging technologies to ensure our systems remain cutting-edge.
• Understand customer needs and assist in translating these to technical product requirements.
• Follow latest DL model trends and push improvements to the data science team (this includes making use of new libraries).

Qualifications

About You:

• Master's or higher degree in Artificial Intelligence, Mathematics, Statistics or an equivalent field.
• Computer vision background and expertise.
• Proficiency with several machine-learning tools, application programming languages and frameworks (e.g., Python, Pytorch, TensorRT, Tensorflow).
• Experience with AzureML, Databricks, AWS or similar and tools like MLFlow.
• Experience with data visualisation and labeling tools such as Voxel51 & Labelstudio or similar.
• Experience with databases (SQL, LakeFS, Azure blob…).
• CUDA experience is a bonus.
• Experience with DL inference on edge devices and GPU benchmarking.
• Track record of completing full development cycle of data science products that were applied in production on large scale.
• In-depth knowledge of data science principles & DL backbones (also mathematically).
• Excellent communication and interpersonal skills.
• Familiarity with relevant industry standards and licensing requirements.
• Proven experience in influencing and communicating effectively with a team.
• Strong problem-solving and troubleshooting skills.

Additional Information

You will have long-term career opportunities, with a globally renowned company and the following:

• Health insurance.
• Pension scheme:
• 2% employee contribution with 4% employer contribution,
• 4% employee contribution with 6% employer contribution,
• 6% employee contribution 8% employer contribution.
• 25 days annual leave.
• Additional long service days.
• International and collaborative working environment.
• Space and support to experiment with new technologies.
• Social events.
• Be part of a mission to transform how we all obtain, use, and reuse the planet's resources to enable a world without waste.
• Inclusive company culture that values diversity, well-being, and strong camaraderie among our teammates.
• Professional training and development: We are passionate about people and seeing them succeed.
• We love innovation, a collaborative environment where idea sharing and thinking outside the box is encouraged.

How to Apply:

If this sounds like you, we would love to hear from you All applications will be managed in the strictest confidence.

TOMRA is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, colour, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristics. Reasonable accommodations will be made and will be provided as requested by candidates taking part in all aspects of the selection process.

• Master's degree or equivalent in a quantitative discipline such as Math, Economics, Statistics, Engineering, Sciences, or equivalent practical experience.
• 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

• 4 years of experience as a people manager within a technical leadership role.
• Experience working with marketing and media data.
• Experience delivering multiple concurrent marketing mix models and Geo-Experiments end-to-end.
• Experience with Cloud products like GCP (Vertex AI) and SageMaker.
• Understanding of Bayesian approaches and modeling frameworks.
• Ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross-functional stakeholders.

Find the user. Find the magic. Connect the two. At its core, marketing at Google starts with the user and ends with technology, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems – from the everyday to the epic, from the mundane to the monumental. And, we approach marketing in a way that only Google can – break the rules, redefine the medium, make the user the hero, and ultimately let the technology speak for itself.

As a Data Science Manager in the Marketing team, you will lead projects, translating business problems into analytical solutions and you will guide your team to implement data science solutions, improve data, develop metrics, and build models for business insights. You also foster knowledge sharing and develop your team's talent.

You will also be a Marketing Mix Modeling (MMM) specialist, who will play a strategic and technical role in driving all things media, marketing, analytics, and partnering with internal teams to evaluate strategic initiatives. Using first-party and third-party data sources, you will create innovative solutions to demonstrate the effectiveness of Google's media investment. At Google-scale, this implies working on our industry's toughest challenges.

• Provide support in media strategy, measurement, and optimization that requires expertise in advanced analytics work, with special focus on MMMs.
• Partner with internal teams in advanced analytics work including data pipelines, experimentation, measurement, and modeling.
• Identify patterns and behaviors that are effective predictors of performance and critical drivers for a successful media plan.
• Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results.
• Develop evaluation frameworks for ML and LLM models, large-scale models, new metrics, and investigate anomalies. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Job Description Summary

At data42, a division of Biomedical Research, our vision is to empower and inspire Novartis' research and development community in harnessing inter-connected multimodal internal and external data in a securely governed platform. We strive to accelerate additional research across a continuum of research, clinical development and medical to unlock insights leading to the discovery and development of new medicines for patients.

Data42 Data Science and Innovation team is currently seeking a highly skilled individual to join our team as a Senior Data Science Expert. As an essential part of the team, you will collaborate with scientists in various disease and functional areas across the organization to advance research and drug development, specifically in our immunology programs.

With a focus on addressing open questions in immunology, your responsibilities will involve collaborating with other data42 scientists to help build a comprehensive platform for our users and stakeholders to make use of, while ensuring proper governance.

If you are passionate about making a significant impact in medical research and are eager to join a dynamic and collaborative team, we encourage you to apply. There are numerous diseases with urgent medical needs, and our goal is to address these challenges and create a lasting impact on global healthcare.

Your responsibilities will include:

• Leading projects and effectively communicating with stakeholders and collaborators.

• Actively participating in pooling and analyzing multimodal clinical trial data to address important scientific questions, such as target discovery, compound prioritization, disease progression and indication expansion, in close collaboration with teams from across Novartis.

• Develop and apply advanced ML and AI algorithms tailored to biomedical data, including deep learning models, to derive actionable insights from complex multimodal datasets.

• Acting as a connector between data resources and project teams, enhancing the generation of hypotheses by sharing insights derived from or applied to data from different drug development pipeline phases.

Role Requirements:

• PhD in data science, machine learning, bioinformatics, computational biology, or a related field, with substantial postdoctoral (or equivalent) experience in academia or the pharmaceutical industry.
• Proficiency in Python, PyTorch, high performance computing, and/or R for statistical programming.
• Proven experience in professional software development practices: code standards, code review, version control, continuous integration, testing.
• Understanding of biology or medicine, demonstrated experience in working with health-related data.
• Proficient in using biostatistics methods for inference and hypothesis testing. Experience with applying state-of-the-art Deep Learning methods.
• Demonstrated ability to work in a cross disciplinary team and present complex data science concepts in digestible terms to diverse scientific audiences.
• Demonstrated strong scientific curiosity, initiative, and learning agility.

Commitment to Diversity & Inclusion:

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together?

Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up:

Benefits and Rewards: Read our handbook to learn about all the ways we'll help you thrive personally and professionally:

Division

Biomedical Research

Business Unit

Universal Hierarchy Node

Location

Ireland

Site

Dublin (NOCC)

Company / Legal Entity

IE02 (FCRS = IE002) Novartis Ireland Ltd

Functional Area

Data and Digital

Job Type

Full time

Employment Type

Regular

Shift Work

No

Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.

Kargo creates breakthrough cross-screen ad experiences for the world's leading brands and publishers. Every day, our 600+ employees bring the power of their creativity and diversity to radically raise the bar on what mobile, CTV, AI, social, and eCommerce can do to wow consumers and build businesses. Now 20 years strong, Kargo has offices in NYC, Chicago, Austin, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland. Humble brag: In 2024, Kargo was recognized as a Best Place to Work by Ad Age and Built In .

Who We Hire

Success takes all kinds. Diversity describes our workforce. Inclusion defines our culture. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, national origin, protected veteran status, disability or other legally protected status. Individuals with disabilities are provided reasonable accommodation to participate in the job application process, perform essential job functions, and receive other benefits and privileges of employment.

Title: Staff Machine Learning Engineer

Job Type: Permanent, Remote

Job Location: Dublin, Ireland

The Opportunity

The Team: The Machine Learning Operations (MLOps) team at Kargo bridges the gap between data science, engineering, and production deployment. Our mission is to design, deploy, monitor, and maintain scalable machine learning and optimization systems that directly contribute to the business's revenue objectives. Collaborating closely with Data Science, Product Management, and Business stakeholders, we focus on delivering robust solutions that optimize auction dynamics (e.g., bid pricing, pacing), ensure accurate predictions of advertising outcomes (CTR, viewability, etc.), and enable advanced recommendations for advertising content (audience targeting and contextual matching).

The Role: The Staff Machine Learning (ML) Engineer will play a crucial role in designing, developing, deploying, and maintaining machine learning models. This individual will work closely with cross-functional teams to ensure the seamless integration of ML solutions into our advertising technology platform. The position requires strong hands-on experience, technical skills, and a deep understanding of machine learning principles and best practices.

The Daily To-Do

• Design, develop, and deploy machine learning models to meet business objectives.
• Implement CI/CD pipelines for seamless model versioning, updates, and deployment.
• Ensure models are scalable, reliable, and optimized for production environments.
• Collaborate with Data Science, Engineering, and Product teams to deliver end-to-end ML solutions.
• Work with stakeholders to integrate models into the AdTech platform.
• Set up monitoring and alerting systems to track model health and identify data/model drift.
• Continuously optimize models for improved efficiency, accuracy, and performance.
• Leverage AWS (EMR, EC2, SageMaker), Snowflake, Databricks, and other cloud tools for ML workflows.
• Optimize data pipelines, incorporating feature stores for enhanced model performance.
• Stay current with industry trends and emerging technologies.
• Contribute to knowledge sharing, code reviews, and process improvements

Qualifications :

• BS/MS in Computer Science, Statistics, or a related field preferred.
• In-depth understanding of machine learning principles and best practices.
• 3+ years of experience in building and deploying machine learning models in production environments.
• Experience building both offline and online training and inference pipelines for real-time systems.
• Strong experience with AWS (S3, EC2, Lambda, SageMaker), Snowflake, and other cloud-based tools for machine learning and data engineering.
• Familiarity with the MLOps stack, including Databricks, Feature Stores, Kubernetes, Kubeflow, MLflow etc
• Expertise in Spark for large-scale data processing and distributed workflows.
• Proficient in Git and version control best practices.
• Highly skilled in SQL and Python; experience with Go is a plus.
• Hands-on experience in automating the provisioning and management of cloud infrastructure.
• Strong interest in advertising, media, analytics, and marketing, with AdTech or digital advertising experience preferred.
• Highly organized, detail-oriented, and able to manage multiple tasks effectively.
• Excellent communication skills, able to convey complex technical concepts to both technical and non-technical audiences.
• Able to work independently and collaboratively within a team environment.

Follow Our Lead

• Big Picture:
• The Latest: Instagram (@kargomobile) and LinkedIn (Kargo)

Join beqom - where tech meets impact

beqom is a high-growth B2B SaaS platform that helps the world's most respected companies make pay fair, transparent, and motivating. Founded in Switzerland and serving enterprises worldwide, our all-in-one solution is built on beqom Pay Intelligence - empowering HR and business leaders to navigate the complexities of compensation, ensure compliance, and unlock the full potential of their people.

If you thrive in a fast-moving, product-led environment and love turning data into measurable results, you'll feel right at home with us.

The Role: Product Owner, Machine Learning

You will be responsible for making both our powerful machine learning and analytics frameworks impactful, intuitive and accessible for non-technical end-users, such as HR professionals and business leaders.

This requires a unique blend: a solid grasp of statistics, metric generation, reporting, and analytics, combined with a proven talent for simplifying technical interfaces and processes.

You will work closely with data scientists, engineers, designers, and customer-facing teams to deliver features that empower our users to achieve pay equity.

What you'll be doing

• Execute and deliver on the roadmap for features focused on machine learning and analytics across all beqom applications.
• Translate complex analytical concepts and statistical outputs into intuitive user interfaces and clear actionable insights for non-technical users.
• Write clear and concise product requirements, user stories, specifications, and acceptance criteria (Jira is your friend).
• Collaborate closely with engineering and design teams throughout the development lifecycle to ensure features are built to specification and meet user needs.
• Manage the product backlog, prioritize features, and make trade-off decisions based on user value, business goals, and technical feasibility.
• Define and analyze key product metrics to measure success, inform future iterations, and demonstrate value.
• Work with the Product Manager and clients to prioritize what makes sense for our SaaS offering given the broader context

What we need

• Bachelor's or Master's degree in a scientific, technical, or quantitative field (e.g., Hard sciences, Computer Science, Engineering, Finance, Economics, Statistics)
• A minimum of 5 years of experience in a Product Management or Product Owner role with a focus on data, reporting, analytics and/or statistics.
• Experience with statistical modelling
• Experience developing functionality with ML and Gen-AI
• Proven track record of defining product requirements and owning a product roadmap within an engineering team.
• Experience in a client-facing role, with the ability to manage stakeholder expectations and handle challenging conversations.
• Excellent analytical and problem-solving skills.

Desirable, but not essential

• Experience in the HR Technology (HR Tech) space, particularly with compensation, analytics, or pay equity solutions.
• Experience with data visualization tools and techniques.
• Familiarity with usability testing and user research methodologies.
• Knows core concepts of model fine-tuning, vector database administration, prompt engineering, and context engineering.

Why Join Us?

• Your career, your design. Unleash your ambition in our dynamic, autonomous environment.
• Drive meaningful change. Build a fairer future for every employee by joining a market leader that is improving the world of work.
• Belong to something bigger. Collaborate with a passionate, diverse and talented team around the globe.

Susquehanna is expanding the Machine Learning group and seeking exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes.

This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.

What You'll Do

• Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and scalable deployment
• Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
• Design and run experiments using the latest ML tools and frameworks
• Develop automation tools to streamline research and system development
• Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behaviour
• Partner with engineering teams to implement and test models in production environments

What we're looking for

• Post-graduate degree in machine learning or a related discipline with publications at top tier conferences, or professional experience proposing novel machine learning algorithms.
• 4+ years experience in building and applying machine learning techniques.
• Demonstrated experience working with and drawing conclusions from large datasets.
• Proficient programming skills in Python and/or C++.
• Practical knowledge of ML libraries and frameworks, such as PyTorch or TensorFlow, especially in production environments
• Hands-on experience applying deep learning on time series data
• Strong foundation in mathematics, statistics, and algorithm design
• Excellent problem-solving skills with a creative, research-driven mindset
• Demonstrated ability to work collaboratively in team-oriented environments
• A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment

If you're a recruiting agency and want to partner with us, please reach out to Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.