Staff Data Scientist

Staff Data Scientist About Us Mutinex is a data and marketing analytics startup transforming the multi-trillion-dollar advertising industry by challenging the traditional consulting-based approach to Market Mix Modelling. We are expanding our team and welcoming experienced talent to collaboratively build our globally used and transformative marketing measurement product suite - GrowthOS, DataOS, MAITE. We empower marketers by helping them to understand the value of their past decisions and the impact of future marketing spend. With offices in Sydney, Melbourne and New York City, we encourage you to work in the way that maximises your performance. What’s the role? We are looking for a Senior/Staff Data Scientist to help grow our uniquely positioned model stack. With a special focus on model and data product development and marketing science, you will take charge of our models in finding ways to improve robustness and streamlining our parameter space. You will also support and lead the scalable and automated deployment of our models and data products for new customers. As a fast growing startup, your work will help refine our data platform by refining its engine: our state-of-the-art marketing investment models. Improving our models and data products will directly contribute to our growth. The mission of our data science team is to be the central nervous system of Mutinex. Day to day Automation of model operations, with a critical focus on quality and customer success. Development of novel models and data products. R&D POC work using contemporary developments in ML, AI, and statistics. Writing: creating documentation for both data science and non-technical stakeholders; providing a data science lens on insights and outputs from the model, processes, and data products. Required qualifications Strong Python - deep knowledge of the standard library, canonical best practices, contemporary trends, and knowledge of multiple ML libraries. Strong principles in software engineering. Strong test-writing discipline. Expertise in Bayesian Statistics. Experience working with multivariate time series data. Experience implementing statistical inference algorithms (e.g., particle-filters, variational inference). Solid understanding of fundamental mathematics for statistics and machine learning - probability theory, linear algebra, and calculus. Machine learning fundamentals. Bachelors/Masters/PhD in statistics, data science, or comparable quantitative degree - e.g. Engineering, Science. Why you should join us We’re improving a multibillion dollar industry with product technology that is disrupting the status quo of consulting based approaches to marketing mix modelling. Although it’s early days, we’re well positioned to win. We’ve got brilliant people, a market leading product, and we are regularly closing household name customers on the strength of our product in the market. As a technology driven data science company we recognise that excellence in engineering will provide an edge that allows us to move faster and build richer more innovative products. We’re putting our money where our mouth is, and investing substantially in the quality of our codebase and platform, and holding a high hiring bar for engineers in our teams. You’ll also be joining a company that’s harnessing the artificial intelligence and data science wave that is currently rolling through the industry. Data is in our DNA, and we’re positioned to join disruptive companies like Snowflake, OpenAI, Fivetran, Amplitude, Segment, Monte Carlo that have garnered multi billion dollar valuations. As we grow there’ll be an opportunity to share in the wealth upside with equity part of your package. The opportunity to work in a data science product company in Australia is not to be passed over lightly. We’d love to hear from you. Department Data Science Locations Sydney office , Melbourne Office Remote status Hybrid About Mutinex Mutinex is the end to end market mix solution that helps marketers, media leads, agencies, analytics and finance teams identify and optimise the different factors that drive sustainable business growth. Founded in 2017 Coworkers 70 and growing!