Job Specifications
About us:
Amach is an industry-leading technology driven company with headquarters located in Dublin and remote teams in UK and Europe.
Our blended teams of local and nearshore talent are optimised to deliver high quality and collaborative solutions.
Established in 2013, we specialise in cloud migration and development, digital transformation including agile software development, DevOps, automation, data and machine learning…
As a key member of a product squad and reporting to the Lead Product Data Scientist, a Data Scientist will develop data pipelines, machine learning models, and complex optimization 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 will ensure that their features integrate seamlessly into the product’s technical stack (data ingestion, user interface, orchestration) as well as the business process and use case (e.g., to maximize impact and value realization).
Required skills
Strong knowledge of either machine learning and optimization techniques, incl. supervised (regression, tree methods, etc.), unsupervised (clustering) learning, 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
Key responsibilities & duties include:
The Data Scientist has full-stack accountabilities across the full value chain of building an industrialized data-science software product:
Understanding a business problem and its component processes end to end, and identifying opportunities to make decisions more optimally leveraging decision-support tooling
Efficiently conducting analyses and visualizations to identify valuable opportunities for decisionsupport and to determine trade-offs between different potential feature implementations
Prototyping advanced machine learning and optimization models to prove the value of a use case and approach (in Python)
Delivering features to industrialize machine learning and optimization 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)
Implementing integrations between the core algorithm (machine-learning or optimization) and a workflow orchestration paradigm such as Dagster
Implementing software in a cloud-based deployment pipeline with Continuous Integration / Continuous Deployment (CI/CD) principles
Building 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 prioritisaion 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 modeling approach, trade-offs, and results with the internal team and business stakeholders
The Data Scientist is also accoun
About the Company
At Amach, we are uniquely positioned to help Airlines lower operational costs while simultaneously driving revenue growth.
What sets us apart is our deep expertise in aviation, an industry where operations, efficiency, and safety are paramount. With more then 300 people in Amach and years of hands-on technology experience, we’ve mastered strategies that not only streamline operations but also maximize revenue streams.
Our aviation background enables us to bring innovative, high-impact solutions to your business, ensuring y...
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