Data Scientist - Customer-facing
Sourse AI
We’re an Aussie-grown AI startup based in North Sydney. We’ve built an innovative decision intelligence platform that is licensed by telcos, energy, and media businesses across Australia, NZ and the Middle East.
It’s an exciting time for you to be joining our team - we’re growing our market and expanding to the Middle East and Europe. To help with the growth, we’re looking for an early to mid-career data scientist to help work with customer data on our platform. You’ll need to have relevant experience in the business application of data science, ideally in the Telco space, a "can-do" attitude and be able to work directly with customers. You’ll learn from some of the best software engineers and data scientists in Australia (there are three PhD-qualified members of our team and three highly experienced data scientists).
In this role you’ll be working with our data science team on analysing customer data, developing new analytical features for our machine learning models and developing new models for customers. Expertise in segmentation or Customer Value Management (CVM) would be very helpful. You will be working directly with our new and existing customers to understand their business needs and requirements and presenting your findings to them.
Day to day, you will be analysing and modelling customer (tabular) data using mostly SQL, Jupyter notebooks and Kubeflow pipelines for deploying the developed models. You will take ownership of end-to-end delivery of models to customers starting from data checks and offline feature and model development to delivering deployment ready feature sets and model artefacts and presenting your findings to customers with support from our Customer Success team.
You will be working on top of the standardised feature mart to test the applicability of existing features and develop new ones for our customers. This will allow you to use existing modelling code and extend it in a reusable way to train and evaluate machine learning models for medium to large commercial datasets to predict customer behaviour. You will help us further develop tools for automating data analysis for finding issues in the data, creating datasets and selecting features for training and testing of models.
If you’re independent, self-directed, conscientious, and care about quality - and you want to work with good people doing cool things we’d love to hear from you.
Responsibilities
- Develop and maintain machine learning models for customers
- Design and deliver new features for models
- Translate complex data insights into actionable narratives tailored for non-technical customers, including executives and marketing teams to drive decision-making
- Develop tools to help us speed up analysis of datasets and help with building ML models
- Help deploy models to production and track their performance
Skills and qualifications
- At least 3 years of professional experience in modelling tabular data in a commercial environment, using Python, and ideally at least one year of experience modelling Telco data
- Strong verbal and written communication skills and interpersonal skills
- Data Storytelling: you can leverage advanced data analysis to craft compelling, client-facing narratives that distill complex findings into actionable insights
- At least 3 years of professional programming experience in Python
- Good theoretical knowledge and solid hands-on experience with machine learning and feature engineering
- Strong experience with SQL
- Solid knowledge of statistics and experience applying it to practice
- Experience working in a cloud environment, ideally Google Cloud
- Experience with software engineering best practices: version control, testing, documentation and clean coding
- Ideally experience working with command line tools
- Ideally experience working with external customers directly