Practice Lead - Data Science_ ML

Infosys; Dublin; On-site; EUR 80,000 - 120,000; Full time

Benefits offered by this job

Competitive compensation including bonuses

Job summary

Infosys is looking for a Practice Lead within Data Science in Dublin, Ireland. As a key player in building and implementing analytics solutions, you will manage teams, drive initiatives, and utilize cutting-edge technologies to deliver impactful results.

The ideal candidate will possess strong analytical skills, hands-on experience with machine learning, and an ability to communicate insights effectively. This position offers opportunities for competitive compensation, including bonuses.

Qualifications

• 5+ years of experience in Data Analytics, Data Science and Machine Learning.
• Bachelor's degree in a quantitative discipline with a consistent academic track record.
• Experience managing client relationships and developing business cases.

Responsibilities

• Understand and translate business requirements into technical specifications.
• Perform data wrangling, model building, and deployment.
• Drive end-to-end data-driven solutions.

Skills

Data Science

Python/R

SQL

Machine Learning

Azure/GCP/AWS

Data Wrangling

Statistical Analysis

Data Visualization

Education

Bachelor of Engineering/Bachelor of Technology

Bachelor's degree in a quantitative discipline

Tools

Azure ML

Databricks

Kubernetes

Job description

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.