Data Scientist - Graduate
Parrot Analytics, New Zealand
Job Description
We love TV. We believe in the magic of content, and its impact on people's lives.
Passionate about TV, data and technology? Join our growing team as we deliver the world’s leading content demand analytics built on the largest demand database to bring science to the art of TV. Rapidly establishing as a global currency in TV, our Demand Expressions are helping to drive a new era of empirical measurement in the industry, as we aim to help our partners make the most powerful decisions, every day.
Parrot Analytics is a content demand analytics company that empowers some of the largest media and entertainment companies, brands and agencies with the world’s largest demand behavior data sets to understand global audience demand for television content. Utilizing the most advanced artificial intelligence platform in the industry, custom machine learning software and our own patents, we provide the measurement of content popularity regardless of the market or broadcast platform we surface insights to our partners both on our dedicated dashboard as well as through our growing partner insights team.
About the Role
We are looking for talented post graduates to join our data science team to support complex data analysis projects using standard modelling and data transformation approaches. This is a 6-month paid internship program, full time at our Auckland office.
You should be comfortable working with very large data sets residing in different data stores in disparate formats and be strong with hands-on implementation, and data visualisation.
We are always on the look-out for great data-storyteller, passionate about product development, and knows how to use its knowledge to create value for our partners. You will have strong ownership of your project and will be working along side UI/UX designers, product manager and data engineers.
Please note: this job is being funded by Callaghan Innovation, and as such, you need to meet certain requirements before we can hire you:
To be eligible for an Ramp;D Career Grant internship, students must:
- Be about to complete, or have recently completed, a masters or PhD degree in science, technology, engineering, design or business ie have submitted a thesis for marking (or completed course requirement for taught masters) less than 12 months ago
- Have undertaken the study at a New Zealand tertiary institution if you are not a New Zealand citizen
- Be legally permitted to work in New Zealand
- Not have been employed as a data scientist under a professional arrangement related to your area of study except temporary, part-time or at a tertiary organisation
- Not have been previously employed at the business unless this was short-term employment (eg over the summer break).
Key responsibilities will include:
- Conduct quantitative and qualitative analysis, including research, data collection, data preparation and exploring it for accuracy
- Application of statistical modeling and optimization techniques most suited to solve business problem (using R, Python, SQL, and/or other relevant tools)
- Implement (and partly design) solutions for a defined data science related problem under the guidance of other experienced data scientists.
- Interpret outputs of statistical models and results to translate input from quantitative analyses into specific and actionable business recommendations and implications
- Providing detailed documentation of modeling techniques, methodologies, assumptions made and process steps
- Manage delivery of analytical solutions via written and verbal presentations
- Identify areas for further investigation as well as creating innovative methods of analysis
Requirements
- Recently completed or in the final year of MSc/PhD in the field of Mathematics, Statistics, Economics, Computer Science, Engineering or related, in New Zealand.
- Expertise in one or more of the following domains is preferred: Natural Language Understanding (NLU), Natural Language Generation (NLG), Natural Language Processing (NLP).
- Ability to write programs in datascience friendly language (R/Python) to prototype and test analytical ideas
- Data visualisation skills/experience (Tableau, PowerBI)
- Strong probability theory and statistics knowledge and some of the main data science algorithms
- Good problem-solving skills
- Good understanding of fundamental Machine Learning algorithms and tool-sets
- Empathy for customers, teammates, and other stakeholders
- Effective communication skills who is able to listen intently and understand the needs of the business and can convert these into clear and easily understood specifications and are able to pre