Stockland

Machine Learning Engineer

Job description

Job Location: Sydney, NSW

Job Title: Machine Learning Engineer

Role: Full time

Company description:
At Stockland we are a community delivering outcomes that benefit the community at large. We work collaboratively and inclusively, building strong working relationships. Our portfolio is diverse and so are the opportunities for professional and career development. We are committed to providing our people with broad experiences to build a successful career.

We recognise the importance of flexibility and work life-quality and over 80% of our employees have informal or formal flexible work arrangements. Additionally, Stockland has a strong commitment to achieving the best outcomes through an inclusive and collaborative culture. Our customers come from diverse backgrounds, and we want our teams to reflect this.
Job Description:

Contribute to a high-performance team by developing, deploying and maintaining automated machine learning and advanced analytics pipelines to enhance business understanding of customer behaviours and needs, optimise business performance, and provide data-led solutions for enhanced portfolio & asset decision intelligence.

Key responsibilities:
  • Work closely with other members of the Data Science & Insights’team and other business stakeholders/clients to scope out and gather requirements for machine learning and advanced analytics solutions
  • Architect and produce SA diagrams for automated machine learning and advanced analytics pipelines utilising cloud infrastructure/services
  • Collaborate with data scientists in the Data Science & Insights’ team and data engineers from the Digital & Emerging Technology team to develop data ingestion and transformation pipelines to support machine learning and advanced analytics solutions
  • Collaborate with data scientists in the Data Science & Insights’team to develop, iterate on, deploy and monitor machine learning models and pipelines
  • Work within and champion agile sprint-based project/workflow management, including weekly team stand-ups and proactive card/board management
  • Evangelise and exemplify best practices for software development/collaboration and machine learning cloud deployments within the Data Science & Insights’ team and across the organisation

About You:
Experience
  • Degree qualified in a technical discipline such as Computer Science, Mathematics/Statistics, Physics etc.
  • 2+ years’ industry experience deploying/productionising machine learning models on cloud services/infrastructure

Skills/Competencies
  • Python (advanced/expert level) - experience with ML related packages (e.g. Scikit-learn, Pandas, XGBoost)
  • SQL (advanced/expert level) - experience with PostgreSQL and PostGIS will be highly regarded
  • Cloud Services/Infrastructure (AWS preferred) - experience deploying ML pipelines in serverless architectures
  • Software Development - object oriented programming, test driven development
  • Code Collaboration and Source Control (Git)
  • Unix/Bash proficiency

Attributes
  • Abstract problem solver and critical thinker
  • Intellectually curious and open minded
  • Ability to tackle problems both autonomously and collaboratively
  • Rigorous attention to detail
  • Strong time and workload management skills
  • Impactful communicator

The Stockland Proposition
At Stockland we are a community delivering outcomes that benefit the community at large. We work collaboratively and inclusively, building strong working relationships. Our portfolio is diverse and so are the opportunities for professional and career development. We are committed to providing our people with broad experiences to build a successful career.
We recognise the importance of flexibility and work life-quality and over 80% of our employees have informal or formal flexible work arrangements. Additionally, Stockland has a strong commitment to achieving the best outcomes through an inclusive and collaborative culture. Our customers come from diverse backgrounds, and we want our teams to reflect this.
We offer competitive remuneration and benefits. Benefits include free to access or subsidised lifestyle, health, well-being and financial services products.

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