Data Scientist Intern

New Aim is Australia's largest and fastest-growing private ecommerce company. Since 2005, we've evolved from marketplace seller to ecommerce enabler, ranking among the 'Top 200 Private Companies' in Australia.

We’re reimagining the possibilities of ecommerce, introducing new technologies to democratise business ownership, and inspiring entirely new categories of business. It’s all possible because of our proprietary technology that improves procurement, supply chain management, multichannel integration, and price decisioning.

We partner with Australia’s most-loved household brands and online marketplaces including Bunnings, Myer, Woolworths, Catch, and MyDeal. Our channel coverage represents more than 60% of Australia’s total retail sales. Through our B2B retail marketplace, Dropshipzone, we’re creating an ecosystem that enables thousands of SMEs to start and scale with ecommerce.

If you're as excited about this as we are: join us! It’s a hell of a ride.

This internship is UNPAID and starts from 15 April 2024 to 24 May 2024. You are expected to attend 5 days per week in our Head Office in Hawthorn East, VIC.

Data Scientist Intern

The Data Scientist Internship position is structured to provide an immersive learning experience in the rapidly evolving field of data science, with a specific focus on the development and application of machine learning models. This internship aims to bridge the gap between academic knowledge and practical skills, offering interns the opportunity to learn directly from seasoned professionals in a real-world e-commerce context. Interns will engage in a structured program designed to introduce them to various stages of machine learning model development, including data preprocessing, feature engineering, model selection, training, evaluation, and refinement. Throughout the program, interns will be encouraged to apply theoretical concepts to practical challenges, gaining hands-on experience with data analysis, statistical methods, and machine learning algorithms. This purposefully educational environment is crafted to foster growth and learning without the expectation of the intern contributing to the company's active projects, aligning with legal standards for unpaid internships. The ultimate goal is to equip interns with a solid foundation in data science that they can build upon in their future careers, while ensuring a comprehensive understanding of the responsibilities and skills of a Data Scientist.

Key Steps & Milestones:

1. Introduction to Data Science at Our Company: Begin the internship with an orientation session focused on the role of data science within our company, highlighting ongoing projects and the impact of data science on decision-making processes.

2. Foundational Training: Engage in a series of workshops and seminars designed to cover essential data science concepts, including statistical analysis, machine learning theory, and an overview of tools and technologies used in the field.

3. Data Exploration and Cleaning: Learn the importance of data quality and how to prepare data for analysis. Interns will practice identifying and correcting issues in data sets, such as missing values and outliers, and learn techniques for data normalization and transformation.

4. Feature Engineering and Data Visualization: Gain hands-on experience in creating meaningful features from raw data and using visualization tools to explore and present data insights. This step is crucial for understanding the data's underlying patterns and relationships.

5. Model Optimization and Evaluation: Learn advanced techniques for improving model performance, such as hyperparameter tuning and cross-validation. Interns will also explore different metrics for evaluating model accuracy, precision, recall, and other relevant performance indicators.

6. Presentation of Findings: Prepare a final presentation to showcase the project's methodology, challenges faced, and the solutions implemented. This presentation is an opportunity for interns to demonstrate their learning and for the team to provide constructive feedback.

Key Selection Criteria

Must:

• At least one year of work or internship experience in an IT-related field.

• Worked in a team with a group-maintained project.

• Fundamental Knowledge: Strong understanding of statistics, probability, and basic machine learning concepts.

• Programming Proficiency: Ability to code in Python, including familiarity with data science libraries such as Pandas, NumPy, and scikit-learn.

• Analytical Thinking: Capacity to think critically and solve problems using data-driven approaches.

• Communication Skills: Effective verbal and written communication abilities to articulate findings and insights.

• Fluent English – Written and Verbal

• Bachelor's or higher degree in IT-related major.

Preferred:

• Bachelor's or higher degree in Computer Science, Information Technology, or Data Science

• Worked in an Agile team

• Experience with Data Visualization Tools: Knowledge of visualization libraries or tools (e.g., Matplotlib, Seaborn, Tableau).

• Familiarity with Advanced Machine Learning: Exposure to more complex machine learning techniques and algorithms.

• Understanding of Data Management: Basic knowledge of SQL and experience with handling large datasets.

• Collaborative Experience: Prior experience working on projects in a team environment, demonstrating teamwork and adaptability.

Relationships and Authorities

Mentor: Data Scientist

Buddy: Data Engineer

To be eligible for an Internship employment with New Aim, candidate must be in Australia on a visa with work rights or be an Australian/New Zealand citizen or permanent resident.