Practice Lead - Data Science and Machine Learning

Role Overview

This position calls for a Practice Lead specializing in Data Science and Machine Learning to be based in Dublin, Ireland. The role involves developing and deploying analytics solutions tailored to client needs, requiring strong numerical aptitude, domain experience, and eagerness to engage with advanced technologies. The compensation package is competitive and includes potential bonuses.

Key Responsibilities

• Comprehend business needs and convert them into precise technical requirements.
• Conduct detailed business analysis to identify problems, prospects, and recommend solutions.
• Manage activities like data processing, predictive model development, and deployment.
• Keep up-to-date with cutting-edge research and technology; share insights company-wide.
• Lead efforts to enhance team morale, unity, and collaboration.

Technical Expertise Required

• Proficiency in Data Science with hands-on experience in Python, R, PySpark, SparkR for Exploratory Data Analysis and predictive model creation involving big data.
• Familiarity with popular machine learning algorithms including clustering, classification, and dimensionality reduction techniques.
• Experience deploying ML-based business transformations such as Demand Forecasting and Price/Promotion Optimization.
• Strong SQL skills and familiarity with relational database management.
• Hands-on experience with cloud platforms like Microsoft Azure, Google Cloud Platform, Amazon Web Services, and tools like Databricks and Snowflake.
• Ability to scale machine learning models beyond proof-of-concept stages.
• Knowledge of Azure services for deployment, including Azure Databricks and Azure DevOps pipeline setups.
• Clear communication of data-driven insights to technical and non-technical stakeholders.
• Capability to lead end-to-end data solutions with effective risk and resource management.
• Sound understanding of statistical principles including distribution properties and hypothesis testing.
• Data examination skills to extract vital information for automation and process optimization.
• Quick learner with enthusiasm to adopt new technologies as needed.

Machine Learning Operations and Engineering Skills

• Expertise in object-oriented programming, adhering to coding standards, architecture design, configuration management, package management, logging, and documentation practices.
• Experience with Test-Driven Development using frameworks such as Pytest, version control with Git, and REST APIs.
• Proficient understanding of Azure ML environment and runtime configurations including cluster management, alerts, and best practices.
• Designing and implementing ML systems and pipelines employing MLOps practices and tools such as MLFlow and Kubernetes.
• Knowledge in event-driven orchestration and deployment of online models.
• Commitment to establishing best practices for MLOps development.
• Strong abilities in data analysis tools—SQL, R, and Python—and understanding of databases and data science concepts.
• Experience liaising with client IT and business teams to gather and translate business requirements for development.
• Competence in client relationship management and business case development.
• Possession of Microsoft Azure AZ-900 certification and knowledge of Azure architecture is advantageous.
• 4-5 years of expert-level object-oriented Python programming experience.
• Practical DevOps knowledge with implementation on at least one or two projects.
• Support in building ML pipelines from initial creation through execution and maintenance.
• Ability to guide development teams on coding standards, debugging pipeline issues, and maintaining documentation.
• Regular interaction with business stakeholders regarding development progress and issue resolution.
• Focus on automation, technology enhancement, and process improvements for deployed projects.
• Establishment and enforcement of standards related to coding, pipeline management, and documentation adherence.
• Compliance with key performance indicators and service-level agreements associated with pipeline operations.
• Commitment to ongoing research on new cloud services and technological advancements.

Additional Skills and Knowledge

• Understanding of at least one industry domain such as Retail, Supply Chain, Logistics, or Manufacturing.
• Familiarity with project lifecycle methodologies, including both waterfall and agile frameworks.

Soft Skills and Personal Attributes

• Excellent verbal and written communication skills to collaborate effectively within teams.
• Strong orientation towards customer satisfaction, ownership, urgency, and proactive attitude.
• Capability to manage multiple priority tasks in a fast-moving work environment.
• Ability to maintain credibility with team members by working collaboratively and professionally.

Experience and Qualifications

• Several years of experience in data analytics, data science, machine learning, and deploying ML solutions.
• Bachelor's degree in Engineering, Technology, or any quantitative field such as Statistics, Economics, Mathematics, or Marketing Analytics with consistent academics.
• Preferred: Master's degree or PhD in Science, Mathematics, Statistics, Economics, or Finance disciplines.

Personal Traits

• Highly analytical mindset with strong initiative and adaptability.
• Exceptional customer focus and commitment to quality.
• Superior communication abilities in both speech and writing.

About the Employer

The company is a recognized global leader in digital services and consulting, enabling clients across more than 50 nations to transform digitally. With over 40 years of experience, the company leads enterprises through their digital journeys by integrating AI-driven core systems and agile digital operations to elevate performance and customer satisfaction. The organization fosters an inclusive environment that values merit, diversity, and equal opportunity for all employees.