Specialist,data Science

**Data Scientist**

**Let’s talk about the team**

Join our Business Process Improvement Team as a Data Scientist to spearhead AI, Machine Learning (ML), and Operations Research (OR) initiatives that enhance operational efficiency and resilience. At ResMed, we’re committed to transforming our huge supply chain and operational processes with an “AI First” approach, driving impactful innovation that optimizes performance, improves responsiveness, and strengthens our business. In this role, you'll work on projects that reshape how we deliver value across our supply chain and operational networks, harnessing data to create cutting-edge solutions that drive growth and impact

**Let’s talk about the role**

As a Data Scientist in the corporate systems domain, you will develop AI/ML/OR models to optimize demand forecasting, financial planning, inventory management, and logistics. You’ll work with global, high-achieving teams to enhance efficiency and innovation in supply chain, logistics, and financial operations. You will deploy your models into production and monitor them using our innovative AI/ML cloud platform. You will communicate insights to a broad audience of stakeholders and leaders.

**Responsibilities**
- Support senior data scientists and engineers in executing well-defined data tasks and analyses
- Work on simpler data wrangling tasks such as cleaning, transforming, and visualizing datasets
- Assist in building and evaluating basic machine learning and optimization models under supervision
- Perform exploratory data analysis (EDA) to uncover trends and insights
- Document processes and methodologies used in projects for future reference
- Communicate findings to internal team members with clear data visualizations
- Participate in team meetings and contribute to discussions around business problems and solutions

**Qualifications and Experience**
- Either: Masters or PhD in computer science, data science, operations research or other quantitative field and 0-2 years of industry experience in Machine Learning Engineering and data science
- Or: 2-4 years of industry experience in data science with demonstrated skills in analysis and basic modeling
- Proficiency in basic SQL for querying databases and performing data manipulations.
- Experience in either Python or R for data manipulation, analysis, and simple modeling.
- Understanding of key statistical concepts, basic machine learning algorithms (e.g., linear regression, decision trees), and operations research methods such as linear and integer programming
- Ability to create data visualizations using tools like Matplotlib and Seaborn.
- Basic familiarity with version control systems like Git.
- Exposure to cloud platforms (AWS, GCP, Azure) or willingness and capability to learn
- Communicate technical results clearly to both peers and non-technical team members.
- Display curiosity and eagerness to learn new tools, methods, and business concepts.
- Ability to take direction and feedback from senior colleagues to improve work quality.
- Demonstrate time management and organizational skills by completing tasks in a timely manner and maintaining clear documentation.
- Willingness to take ownership of smaller-scale tasks while contributing to larger team projects.

**What you can expect**
- A supportive environment that focuses on people development and best practice implementation
- Opportunity to design, influence and be innovative
- Work with inclusive global teams and the open sharing of new ideas. We want your ideas
- Be supported both inside and outside of the work environment
- The opportunity to build something meaningful and see a direct positive impact on people’s lives