Practice Lead Data Science ML IRL

Job Description
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.
Bachelors 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.