Role - 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 to our esteemed clients. The incumbent should have strong aptitude for numbers, experience in any domain and willingness to learn some cutting edge technologies.
Roles & Responsibilities:
- Understand the requirements from the business and translate it into an appropriate technical requirements.
- Creating a detailed business analysis, outlining problems, opportunities and solutions for a business.
- Perform activities related to data wrangling, model building and model deployment.
- Stay current with the latest research and technology and communicate your knowledge throughout the enterprise.
- Lead initiatives to improve the team morale, camaraderie, and collaboration
Technical Skills:
Must Have Skills (Data Science/Machine Learning):
- Hands-on experience in Data Science, Python/R, PySpark/SparkR Coding and associated state of the art technologies for Exploratory Data Analysis, building predictive models with big data. Familiarity with standard Clustering, Classification, dimensionality reduction and other techniques/Algorithms in Machine learning.
- Experience in 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
- Scaling ML Models from POC phase.
- List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup
- Ability to communicate actionable insights using data, often to a non-technical audience.
- Ability to drive end-to-end data driven solutions with excellent sense of risk and resource management in any given situation
- Good knowledge on statistical concepts such as properties of distributions, statistical tests and their proper usage.
- Analyze and extract relevant information from large amounts data to help in automating the solutions and optimizing key processes.
- A quick and enthusiastic learner (must) and who is willing to work on new technologies depending on requirement.
Must Have Skills (Machine Learning Operations / Machine Learning Engineer)
- Object oriented programming, coding standards, architecture & design patterns, Config management, Package Management, Logging, documentation
- Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIs
- Azure ML best practices in environment management, run time configurations (Azure ML & Databricks clusters), alerts.
- Experience designing and implementing ML Systems & pipelines, MLOps practices and tools such a 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 requirement and converting into requirement for development team
- Experience in managing client relationship 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
- List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup
- Assist team to coding standards (flake8 etc)
- Guide team to debug on issues with pipeline failures
- Engage with Business / Stakeholders with status update on progress of development and issue fix
- Automation, Technology and Process Improvement for the deployed projects
- Setup Standards related to Coding, Pipelines and Documentation
- Adhere to KPI / SLA for Pipeline Run, Execution
- Research on new topics, services and enhancements in Cloud Technologies
Other key to have Skills:
- Understanding of any one of domain (Eg: Retail, Supply chain, Logistics, Manufacturing).
- Understanding of the project lifecycles: waterfall and agile.
Soft Skills:
- Strong verbal and written communication skills with 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 the 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, Economy and Finance with consistent academic track record.
- PhD in any stream.
Personal
Besides the professional qualifications of the candidates we place great importance in addition to various forms personality profile. These include:
- High analytical skills
- A high degree of initiative and flexibility
- High customer orientation
- High quality awareness
- Excellent verbal and written communication skills
Overview
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation.
With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.
