Role
Title: Practice Lead – Data Science
Technology: Data Science / Machine Learning
Location: Dublin, Ireland
Compensation: Competitive (including bonus)
Role Summary
We are looking for candidates to build and implement analytics solutions for our esteemed clients. The incumbent should have a strong aptitude for numbers, experience in any domain, and willingness to learn cutting‑edge technologies.
Roles & Responsibilities
Understand requirements from the business and translate them into appropriate technical requirements.
Create a detailed business analysis, outlining problems, opportunities and solutions.
Perform data wrangling, model building and model deployment activities.
Stay current with the latest research and technology and communicate your knowledge throughout the enterprise.
Lead initiatives to improve team morale, camaraderie, and collaboration.
Technical Skills – Must Have (Data Science / Machine Learning)
Hands‑on experience in Data Science, Python/R, PySpark/SparkR coding and state‑of‑the‑art technologies for exploratory data analysis, predictive modeling with big data. Familiarity with standard clustering, classification, dimensionality reduction and other machine‑learning techniques/algorithms.
Experience building and implementing ML‑driven business transformation use cases such as demand forecasting, price/promo optimization, etc.
SQL knowledge and experience working with relational databases.
Hands‑on MS Azure/GCP/AWS cloud, Databricks/Snowflake, SQL knowledge.
Scalability of ML models from POC phase.
List Azure services required for deployment, Azure Databricks and Azure DevOps setup.
Ability to communicate actionable insights using data to a non‑technical audience.
Ability to drive end‑to‑end data‑driven solutions with excellent sense of risk and resource management in any situation.
Good knowledge of statistical concepts such as properties of distributions, statistical tests and their proper usage.
Analyze and extract relevant information from large amounts of data to help automate solutions and optimize key processes.
A quick and enthusiastic learner (must) and who is willing to work on new technologies depending on requirements.
Technical Skills – Must Have (Machine Learning Operations / Machine Learning Engineer)
Object‑oriented programming, coding standards, architecture & design patterns, configuration management, package management, logging, documentation.
Experience in Test‑Driven Development and use of Pytest frameworks, Git version control, REST APIs.
Azure ML best practices in environment management, runtime configurations (Azure ML & Databricks clusters), alerts.
Experience designing and implementing ML systems & pipelines, MLOps practices and tools such as MLFlow, Kubernetes, etc.
Exposure to event‑driven orchestration, online model deployment.
Contribute towards establishing best practices in MLOps systems development.
Proficiency with data analysis tools (e.g., SQL, R & Python).
High‑level understanding of database concepts/reporting & data science concepts.
Hands‑on experience in working with client IT/Business teams in gathering business requirements and converting them into requirements for the development team.
Experience managing client relationships and developing business cases for opportunities.
Azure AZ‑900 certification with Azure architecture understanding is a plus.
Expertise in Object‑Oriented Python programming with 4‑5 years’ experience.
DevOps working knowledge with implementation experience – 1 or 2 projects a minimum.
Hands‑on MS Azure / GCP/AWS cloud knowledge.
Help team with ML pipelines from creation to execution.
Assist team to maintain coding standards (flake8, etc).
Guide team to debug pipeline failures.
Engage business/stakeholders with status updates on progress of development and issue fix.
Automation, technology and process improvement for deployed projects.
Setup standards related to coding, pipelines and documentation.
Adhere to KPI/SLA for pipeline run, execution.
Research new topics, services and enhancements in cloud technologies.
Other Key To Have Skills
Understanding of any one of the domains (e.g., retail, supply chain, logistics, manufacturing).
Understanding of the project lifecycles: waterfall and agile.
Soft Skills
Strong verbal and written communication skills and the ability to work well in a team.
Strong customer focus, ownership, urgency and drive.
Ability to handle multiple, competing priorities in a fast‑paced environment.
Work well with team members to maintain high credibility.
Work Experience
Years of experience in Data Analytics, Data Science and Machine Learning, Machine Learning deployments.
Educational Requirements (any of the following)
Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record.
Bachelor's degree in a quantitative discipline (e.g., statistics, economics, mathematics, marketing analytics) or significant relevant coursework with consistent academic track record.
Additional Academic Qualification (good to have)
Masters in any area related to science, mathematics, statistics, economics and finance with consistent academic track record.
PhD in any stream.
Personal
High analytical skills.
A high degree of initiative and flexibility.
High customer orientation.
High quality awareness.
Excellent verbal and written communication skills.
Infosys is a global leader in next‑generation digital services and consulting. All aspects of employment at Infosys are based on merit, competence and performance. Infosys is proud to be an equal‑opportunity employer.
#J-18808-Ljbffr