Due to internal promotion, we are looking for another talented Data Scientist to work with our customers' data in our Model Scale team.
The work this team does is vital to our business, as you will analyze our customers' Marketing, Media, and Sales Data and leverage the insights gained to configure our generalized model to surface critical business insights for customers in our core product, GrowthOs.
This means this team isn't doing deep model R&D but managing refreshes, configuring, diagnosing, and calibrating models and becoming industry subject matter experts to contextualize model performance to our customers' industry nuances. Mutinex is an early-stage SaaS MarTech startup that is already working with some of Australia and the world's largest brands.
We have a hybrid way of working, doing a few days a week in the office, which is a short walk from Central station in Sydney.
About the Role You will work alongside our Account Managers, Data Engineers, Data Scientists, and Marketing Scientists to take our latest modeling innovations and apply them to help our customers make effective marketing investment decisions.
You will collaborate closely with our R&D and Product teams to surface model workflows and feature engineering pipeline improvements.
Your day-to-day will consist of:
Perform exploratory data analysis of a variety of customer and external datasets to understand the customer's business, surface high-signal data, and find opportunities for automating data quality assessments.Apply, diagnose, and configure our state-of-the-art model to solve our customers' problems.Develop expertise in new domains, understanding industry nuances and contextualizing model performance.Be a collaborative team member, working with stakeholder teams to improve processes and suggest model workflow and feature pipeline improvements.What we are looking for The key requirements for this role:
Prior experience in similar Data Science, Customer Data Science, or Data Analyst roles, preferably in startups or tech companies.Proficiency in Python, experience with libraries such as Pandas and NumPy.Manipulating data.Exploratory data analysis.Debugging code.Proficiency with SQL to be able to extract and explore large and complex data sets.Experience with git.Proven ability to manage multiple projects at once while maintaining a high level of attention to detail as well as communicating deadlines at risk of not being met.A strong and proactive communicator; this role is cross-functional and plays a key part in ensuring customers are getting value out of our product.The bonus skills and experience we get excited to see:
Demonstrable experience with Time series data and models is also preferred while experience with Bayesian statistics/models and Media Mixed Modelling (MMM).Experience engineering new features and building and optimizing model workflows (using open-source modeling libraries such as Scikit-Learn, XGBoost, or Statsmodels, etc.) to solve business problems.Understanding of machine learning principles.Summary of role requirements: Flexible hours available.More than 4 years of relevant work experience required for this role.Working rights required for this role.Expected start date for role: 30 October 2024. #J-18808-Ljbffr
