Data Scientists London, England, United Kingdom

Build the Future of Air Travel with Amach

Join one of the world’s fastest-growing technical teams, where innovation meets impact. We take the time to understand your skills, ambitions, and what truly drives you—because your journey matters.

Amach is an industry‑leading technology‑driven company headquartered in Dublin with remote teams in the UK and Europe. Our blended teams of local and nearshore talent deliver high quality and collaborative solutions.

Founded in 2013, we specialise in cloud migration, agile software development, DevOps, automation, data and machine learning, and digital transformation.

As a key member of a product squad reporting to the Lead Product Data Scientist, a Data Scientist will develop data pipelines, machine learning models and complex optimisation models in the ODS software product suite. The Data Scientist is in charge of modelling and robust implementation of features contributing to an operations decision‑support product. In developing a product’s core algorithm, the full‑stack Data Scientist role ensures that features integrate seamlessly into the product’s technical stack (data ingestion, user interface, orchestration) as well as the business process and use case.

Required Skills

• Strong knowledge of machine learning and optimisation techniques, including supervised (regression, tree methods, etc.), unsupervised (clustering), and operations research (linear, mixed integer programming, heuristics)
• Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‑learn, pandas, numpy, gurobi, etc.) to solve real‑life problems and visualise the outcomes (e.g., seaborn)
• Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g., MLflow)
• Experience with cloud‑based ML tools (e.g., SageMaker), data and model versioning (e.g., DVC), CI/CD (e.g., GitHub Actions), workflow orchestration (e.g., Airflow/Dagster) and containerised solutions (e.g., Docker, ECS) nice to have
• Experience in code testing (unit, integration, end‑to‑end tests)
• Strong data engineering skills in SQL and Python
• Proficient in use of Microsoft Office, including advanced Excel and Powerpoint skills
• Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights
• Understanding of the trade‑offs of different data science, machine learning, and optimisation approaches, and ability to intelligently select which are the best candidates to solve a particular business problem
• Able to structure business and technical problems, identify trade‑offs, and propose solutions
• Communication of advanced technical concepts to audiences with varying levels of technical skills
• Managing priorities and timelines to deliver features in a timely manner that meet business requirements
• Collaborative team‑working, giving and receiving feedback, and always seeking to improve team processes

Accountabilities

• Understand a business problem and its component processes end to end, and identify opportunities to make decisions more optimally leveraging decision‑support tooling
• Efficiently conduct analyses and visualisations to identify valuable opportunities for decision‑support and to determine trade‑offs between different potential feature implementations
• Prototype advanced machine learning and optimisation models to prove the value of a use‑case and approach (in Python)
• Deliver features to industrialise machine learning and optimisation models in Python using best‑practice software principles (e.g., strict typing, classes, testing)
• Build automated, robust data cleaning pipelines that follow software best‑practices (in Python)
• Implement integrations between the core algorithm (machine‑learning or optimisation) and a workflow orchestration paradigm such as Dagster
• Implement software in a cloud‑based deployment pipeline with Continuous Integration / Continuous Deployment (CI/CD) principles
• Build logging, error handling, and automated tests (e.g., unit tests, regression tests) to ensure the robustness of operationally critical decision‑support products
• Deliver features to harden an algorithm against edge cases in the operation and in data
• Conduct analysis to quantify the adoption and value‑capture from a decision‑support product
• Engage with business stakeholders to collect requirements and get feedback
• Contribute to conversations on feature prioritisation and roadmap, with an understanding of the trade‑off between speed vs. long‑term value
• Understand and integrate the product into existing business processes, and contribute to the development and adoption of new business processes leveraging a decision‑support product
• Communicate feature and modelling approach, trade‑offs, and results with the internal team and business stakeholders

Ways of Working

• Using Git‑versioning best practices for version control
• Contributing and reviewing pull‑requests and product / technical documentation
• Giving input on prioritisation, team process improvements, optimising technology choices
• Working independently and giving predictability on delivery timelines
• Systems thinking
• Detail‑oriented while understanding the big picture
• Curious, self‑motivated, proactive, and action‑oriented
• Creative and innovative
• Resilient and flexible in light of changing priorities and approaches
• Data‑driven
• Pragmatic
• A true believer in the power of using data to drive better decision making
• A technologist, interested in keeping up with the latest and greatest in software development, optimisation, and machine learning
• Commitment to delivering business value

What’s in it for you

• An opportunity to join a fast‑growing company
• Options for career advancement
• Learning and development opportunities
• Flexible working environment
• Competitive salaries based on experience

Equal Opportunity Employer

Amach is an equal opportunity employer and makes employment decisions on the basis of merit. We celebrate diversity and are committed to creating an inclusive environment for all employees. This job description is intended to convey essential responsibilities and qualifications for this role, but it is not an exhaustive list of tasks that an employee may be required to perform.

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