Company Overview

Founded in 2014, and listed on the ASX since 2015, Superloop’s purpose is to enable better internet for Australian homes and businesses, by enabling challenger retail brands to take a larger share of the market, leveraging Superloop’s Infrastructure-on-Demand platform.

Superloop operates in three segments of the market: consumer connectivity, business network and security solutions, and wholesale connectivity, all of which leverage Superloop’s investments in physical infrastructure assets including fibre, subsea cables and fixed wireless, as well as Superloop’s software platforms. Hundreds of thousands of homes and businesses rely on Superloop every day for their connectivity needs.

Visit www.superloop.com to learn more.

Business Unit Overview

The Strategy and Transformation team develop strategies and implement tools, systems, and processes to drive long-lasting business value and performance for Superloop. There are five key pillars to the Strategy and Transformation team including: data and analytics; strategy; transformation; PMO; and mergers and acquisitions. If you have a passion for making significant change and solving complex challenges in the telecommunications industry, come join our team at Superloop.

Role Purpose and Accountabilities

The Data and Analytics team is a fast-growing team and is currently seeking an experienced Data Scientist to join our dynamic team. In this role, you will play a pivotal role in leveraging your expertise to derive valuable insights from our data ecosystem. Your responsibilities will include:

Lead the Data Science practice within the team: Take charge of developing the data science roadmap, build and productionise new models for business consumption as well as supporting the business with automation and insights. Act as a liaison between data analysts and system developers, fostering collaboration with cross-functional teams to comprehend data requirements and design effective data solutions.

Build and maintain advanced analytical models: Develop and implement cutting-edge data science models to extract meaningful patterns and trends from complex datasets. Utilise machine learning techniques to create predictive models (e.g. churn propensity) and contribute to the development of innovative analytical solutions.

Support the business with Automation: develop and implement automation solution using python and AWS services, including the establishment and execution of automation data flows through APIs.

Collaborate on data engineering initiatives: Work closely with the data engineering team to build and maintain data pipelines, ETL processes, and data ingestion workflows. Ensure the accuracy, completeness, and reliability of data by performing profiling, cleansing, and transformation processes.

Optimise data performance and security: Monitor and enhance the performance of our data ecosystem, promptly addressing any issues or bottlenecks that may arise. Uphold data security, compliance, and governance standards, including encryption, access controls, and audit trails.

Support analytical needs: Collaborate with data analysts to provide them with clean, well-structured data to support their analytical endeavours.

Stay abreast of industry best practices: Keep up-to-date with the latest advancements in data science and analytics, incorporating emerging technologies and best practices to continually improve our data science processes.

This role offers an exciting opportunity to contribute to the growth and success of our Data and Analytics team by applying your expertise in data science and analytics. If you are passionate about leveraging data to drive business decisions and thrive in a collaborative, innovative environment, we invite you to join our team.

Key Deliverables

Key deliverables for this role include:

Conduct data profiling, cleansing, and transformation to ensure data accuracy and reliability.

Create predictive models using machine learning techniques to support decision-making.

Optimize and monitor the performance of the data ecosystem, addressing issues promptly.

Collaborate with data engineers to design and implement scalable data solutions.

Provide clean and well-structured data to support the analytical needs of data analysts.

Lead the development of the data science roadmap, execution timeline, and system strategy.

Act as a conduit between data analysts and system developers, ensuring effective collaboration.

Stay abreast of advancements in data science and analytics to continuously improve processes.

Contribute to the growth and success of the Data and Analytics team by applying expertise in data science.

Qualifications and Experience

Bachelor’s degree in computer science, software engineering, Information Technology, or a related field (or equivalent work experience).

Proven experience as a Data Scientist, with a strong focus on machine learning and productionising models on cloud infrastructure.

Proficiency in AWS services including Redshift, SageMaker, Lambda, S3 and SQS.

Strong SQL skills for data querying, manipulation, and optimization.

Proficiency in Python for scripting and automation of data processes and experience with distributed computing frameworks such as Apache Spark/Hadoop (Proficiency in Scala is a plus point).

General DevOps related knowledge and Knowledge of containerization technologies such as Docker and basic Network Engineering skills. Experience with Kubernetes is a plus.

Experience working with large volumes of data and complex data models.

Knowledge of Data Governance strategies, frameworks, and tooling.

Proficiency with Data orchestration tools such as Apache Airflow, Dagster, Prefect, Luigi, etc.

Experience with Git and coding in collaborative environments

Excellent problem-solving skills and attention to detail.

Strong communication and collaboration skills to work effectively with cross-functional teams.

Experience with telecom industry preferred.