Data & Analytics Engineering – Machine Learning Engineer

Location: Waterford, Ireland, Hybrid 2 Days onsite only

Type: 12 Months of Contract possible to extend or hire

Job Summary:

Design, develop, support, deploy and/or test and influence leading data science and machine learning solutions of medium scale that are high-quality, innovative, efficient, creative, scalable, adaptable, dynamic, fully performing and comply with all standards and best practices in support of business and Client outcomes and objectives. Work independently and applies leading data and analytical skills, tools, practices, and techniques to all deliverables. Exhibits leading understanding of data and analytical concepts such as: data modeling, development, testing, governance, security, performance, DevSecOps, data administration, data technologies, agile planning, and focused on learning more about these domains and continuously honing their craft. Lead across U.S. IT and business groups our strategy of realizing business value from data and utilizing data as a strategic asset. Ability to focus on task at hand, follow-through on prescribed plan with ability to be flexible and think under pressure. Highly motivated team player with a strong desire to learn, grow, and continuously improve.

High Level Job Responsibilities:

• Design, develop, install and/or test leading data science and machine learning solutions that are high-quality, innovative, efficient, secure, creative, scalable, adaptable, dynamic, fully performing and comply with all standards and best practices in support of business and Client outcomes and objectives
• Drive U.S. IT and U.S. business groups to deliver data-informed product strategies
• Help make data more useful and accessible for consumers of data
• Execute full software and product development life cycle (SDLC) and lead continuous improvements leveraging Agile best practices
• Develop leading deliverables to deliver value generating data solution(s) seeking business and Client feedback across U.S. IT and business groups
• Write advanced well-designed, testable, flexible, and scalable data science and machine learning models and supporting code
• Transform and map data from source to destination using various technology solutions
• Produce specifications and determine operational feasibility
• Develop leading software verification (testing) plans and quality assurance procedures
• Document and maintain leading technical solution functionality
• Troubleshoot, debug, and upgrade existing systems
• Deploy leading programs and evaluate business and Client feedback
• Ensure data solutions are updated with latest features
• Participate in code reviews, ability to sign off on large features, and validate vulnerability fixes
• Ability to write functional specifications for large features
• Lead improvements to data product quality, performance, reliability, and scale within domains
• Effectively mentor other engineers
• Proactively improve application performance, reliability, and scale
• Augment existing data sets with other data sources (i.e. external) to make reusable data assets
• Awareness of industry trends, vendors, tools, and other technology solutions to influence architectural design and decisions

1. Lead a "data-first" approach to problem solving and designing IT solution

Mandatory requirements:

Data Scientist or Machine Learning Engineer - Developers – Software Development environment, so must be proficient in Python & R coding / development. Developing ML solutions with Python & R.

Key Skills:

• Leading data science, machine learning models and IT solutions development (programming) foundation.
• Proficiency in Python and R programing languages.
• Strong ability in utilizing data science platforms (Dataiku a distinct advantage) along with Linux, container and AWS based environments.
• Knowledge in AI and GenAI based development patterns (for example: RAG).
• Ability to apply leading testing skills, tools/frameworks, techniques, processes, and principles to software solutions in support of defect management, automation, diagnosis, deployment and reporting in a complex production environment; writes and executes test plans
• Ability to collaborate on, drive and deliver data-informed product strategies
• Improve data quality, application and database performance, reliability, and scale
• Effectively utilize, influence, and lead multiple data model and data development and deployment methodologies, processes, development best practices and DevSecOps and DataOps principles
• Remain current with technology trends and influence change across U.S. IT
• Leading understanding of data governance, data protection, privacy, and security best practices
• Participate in data modeling and data analysis, development and testing, ability approve the design on medium data product features, and validate vulnerability fixes
• Ability to write data mapping and metadata specifications for medium features
• Technically minded problem solver