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- Tasks: Join our team to develop data pipelines and machine learning models that drive impactful decisions.
- Company: Amach, a leading tech company with a focus on innovation and collaboration.
- Benefits: Enjoy flexible working, competitive salaries, and opportunities for career growth.
- Why this job: Be at the forefront of technology, shaping solutions that make a real difference.
- Qualifications: Strong Python skills and knowledge of machine learning techniques are essential.
- Other info: Join a diverse team committed to inclusivity and continuous learning.
The predicted salary is between 28800 - 48000 £ per year.
Amach is an industry-leading technology driven company with headquarters located in Dublin and remote teams in the 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
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 decision support 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 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 modeling approach, trade-offs, and results with the internal team and business stakeholders
The Data Scientist is also accountable for ways of working fit for an Agile cross-functional development squad, including:
- Using Git-versioning best practices for version control
- Contributing and reviewing pull-requests and product/technical documentation
- Giving input on prioritization, team process improvements, optimizing 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, optimization, and machine learning
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.
If you are passionate about driving customer success, advising on strategic solutions, and contributing to product innovation, we would love to hear from you!
At Amach, we strive to be an inclusive community of open-minded individuals with different backgrounds and we are committed to fostering, cultivating and preserving a culture of diversity, equity and inclusion. We strongly believe that a diversity of experience and background is essential to create a fulfilling environment and better solutions for our people and our customers. All Amach employees and contractors are expected to honour this policy and act to ensure that every individual is respected in the workplace.
Your personal data will be processed in accordance with the EU's General Data Protection Regulation (GDPR). We will comply with data protection law and principles, which means that your data will be:
- Used lawfully, fairly and in a transparent way
- Collected only for valid purposes and not used in any way that is incompatible with those purposes
- Relevant to the purposes we have told you about and limited only to those purposes
- Accurate and kept up to date
- Kept only as long as necessary for the purposes we have told you about
- Kept securely
If you would like to contact us about your data, please use the following address: info@amach.com
Data Scientists employer: Amach
Contact Detail:
Amach Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientists
✨Tip Number 1
Network like a pro! Reach out to your connections on LinkedIn or attend industry meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those involving machine learning and optimisation. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and coding challenges. Practice explaining your thought process clearly, as communication is key in collaborative environments like Amach.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, keep an eye on our careers page for new opportunities that match your skills and interests.
We think you need these skills to ace Data Scientists
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Scientist role. Highlight your experience with machine learning, Python, and any relevant projects that showcase your skills. We want to see how you fit into our team!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've used data science techniques to solve real-life problems. This will help us understand your practical experience and how you can contribute to our projects.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use straightforward language and avoid jargon unless necessary. We appreciate a well-structured application that makes it easy for us to see your qualifications.
Apply Through Our Website: We encourage you to apply directly through our careers page. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Amach
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and machine learning libraries like scikit-learn and pandas. Brush up on your cloud platform knowledge, particularly AWS, as it’s a key part of the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex data problems. Be ready to explain your thought process and the techniques you used, whether it was regression analysis or optimisation models. This will demonstrate your analytical skills and ability to apply theory to real-world scenarios.
✨Communicate Clearly
Since the role involves explaining technical concepts to non-technical stakeholders, practice articulating your ideas clearly and concisely. Use simple language to describe your projects and the impact they had, ensuring that even those without a technical background can understand your contributions.
✨Emphasise Collaboration
Highlight your experience working in cross-functional teams and how you’ve contributed to team processes. Discuss any feedback mechanisms you’ve implemented or participated in, as this shows you value collaboration and continuous improvement, which is crucial for the Agile environment at Amach.
