At Slyp we are in the business of customer experience. We think it's crazy that you pay with a smartphone but still receive a centuries old paper receipt. Traditional receipts are nothing but a burden to customers and outside of a proof of purchase, they provide no value to retailers or consumers. We are dedicated to creating world-class technology and helping the environment, one receipt at a time. That's why we have invented the Slyp Smart Receipt.
Why is Slyp a great place to work?
Slyp Village attracts top-notch talent from around the globe. Our inclusive environment allows Slypsters to unleash their creativity and drive, all while being part of a movement that's shaking things up for the better.
Here are some of our benefits:
- Employee Stock Ownership Program (ESOP)
- Generous L&D program - $1500 budget per anniversary for you to use towards honing your craft
- Slyp Gives - we run 2 community give back days each year
- Competitive leave policies including parental leave
- Flexible work and the option to work from anywhere in the world for a period of time
- Sweet pet friendly office, monthly (sometimes random) lunch and learns and always on team fun and experience program
What we are looking for
You should have strong mathematical and numeracy skills and a good understanding of SQL, ETL frameworks, and website scripts. You will explore and analyse data to forecast and optimise capabilities, build data-driven products, and design and maintain key data assets. You will help with designing, implementing, and optimising data pipelines.
Your activities will include prototyping new algorithms, presenting and visualising data, consulting with strategic partners, performing statistical analysis, forecasting trends, and completing ad-hoc analysis. You will also provide mathematical modelling and analysis capabilities to support other business teams.
What does a normal day look like?
Data Modelling and Analysis:
- Utilise statistical analysis to extract valuable insights
- Develop predictive models to improve business processes and decision-making.
- Exploration in machine learning is a plus
Reporting and Visualisation:
- Create and maintain dashboards and reports for internal and external stakeholders
- Communicate findings effectively to help guide business strategies
- Continuously optimise data pipelines for efficiency, scalability and cost
- Work on data engineering best practices to ensure the infrastructure is robust and reliable
Data Quality Assurance:
- Implement data quality checks and monitoring to ensure accuracy and consistency of the data
- Troubleshoot and resolve data-related issues as they arise
- Develop and maintain data pipelines to collect, cleanse, and organise data from various sources
- Ensure data privacy and security standards are adhered to and implement necessary safeguards
What experience or knowledge you will bring to the team
- Bachelor's or higher degree in Computer Science, Data Science, Information Systems, Economics or a related field.
- Familiarity with AWS data services (e.g., Glue, Redshift, Quicksight, Athena, S3, Sagemaker).
- Familiarity with other AWS services is a plus (e.g., Lambda, Kinesis, DMS, IAM, KMS).
- Proven experience in data engineering, including SQL, Python, ETL processes and data modelling.
- Experience in working with large datasets and data warehousing solutions.
- Familiarity with machine learning techniques and tools is a plus.
And what other experience or knowledge would help, if you have it!!
- Previous experience in a similar role in the tech or fintech industry is a plus.
- Previous experience in data analytics for the retail industry is highly desirable.
Our recruitment process
1. Screening phone call with our People Partner
2. Technical Interview with Senior Engineering Manager
3. Interview with Engineering and Data Leads
4. Final Interview with CTO and Co-Founder
Due to our hybrid working model, we are currently unable to accept applications for remote work. We will only be considering candidates based in Sydney, NSW.