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The Industry Solutions Delivery (ISD) Engineering & Architecture Group (EAG) is a global engineering consulting organisation that supports our most complex and leading-edge customer engagements in improving their business performance with the power of Data & AI. EAG develops approaches, innovative solutions, and engineering standards to set our delivery teams and customers up for long-lasting success. We are committed to Responsible AI, and we help our customers build and operate ethical, transparent and trustworthy AI solutions. We are hiring a Data Scientist with deep experience in advanced statistical data analysis, machine learning and artificial intelligence.
Job Responsibility:
Leverage data science and business domain knowledge to improve business performance, evaluate project plans, communicate business goals, and share insights with stakeholders
Acquire, prepare, and explore data through querying, visualisation, reporting techniques, and collaboration with other teams, ensuring data integrity
Apply machine learning and statistical analysis to develop models, train, optimise, and evaluate them, and communicate findings to stakeholders
Test, review, and improve models by analysing performance, incorporating feedback, and contributing to the review process
Write and debug efficient and scalable code while collaborating with engineering teams and integrate data models into customer systems
Understands big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, AML, and REST API consumption/development
Demonstrates a strong commitment to Responsible AI, supporting customers, partners and internal stakeholders in building trustworthy AI solutions.
Requirements:
Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Operations Research, or a related field
4 years of data science experience in business context
Ability to work independently, solve complex data science problems, design and code maintainable and scalable solutions, and effectively apply data science to business challenges
Hands-on software engineering experience (e.g. Python, Scikit, PyTorch, C++) with main established data science frameworks
Familiarity with building and deploying largescale AI solutions into production within a cloud environment
Experience dealing with internal and external stakeholders on large, complex projects.
Nice to have:
Familiarity with building and deploying largescale AI solutions into production within a cloud environment
Experience dealing with internal and external stakeholders on large, complex projects.