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Apple's Sales organisation generates the revenue needed to fuel our ongoing development of products and services. This, in turn, enriches the lives of hundreds of millions of people around the world. Our sales team is, in many ways, the face of Apple to our largest customers.
As the Insights Scientist, you will be instrumental in crafting, implementing, and operating the next generation of analytical solutions for the ANZ Apple Channel Sales team. Analytics is a team sport, and your role will be a key part of a data-centric team that delivers insights that have direct and measurable impact on Apple Sales and its customers.
Description
- Augment existing data solutions from a 'interpret the news' platform to a 'create the news' platform by crafting analytical experiences that simplify data into insights and decision-making by leveraging innovative next generation solutions
- Lead the technical build and enhancement of AI-driven analytical platforms, converting raw and unstructured data into meaningful cause-and-effect insights that inform strategic sales and operational improvements across the organisation.
- Employ predictive modelling, data visualisation, and statistical analysis techniques to build end-to-end solutions for internal collaborators, using sales performance data, market data, programs, and external data to enable our teams to 'move fast' to determine the success and roll-out of Sales Plays
- Collaborate and influence stakeholders and cross-functional partners on the translation of business problems and questions into data science models.
- Work closely with other members of a data-centric team to execute on analyses as well as contribute to the exploration, development, execution, and measurement of analytical solutions that are critical to running the business.
- Apply expertise in data wrangling and preparation to extract, clean, transform, and validate data from multiple systems, creating reliable datasets for analysis, modelling, and visualisation.
- Support experimentation and A/B testing for new insight types and interaction methods.
- Act as a data translator - successfully bridging analytics and business, with the ability to speak the language of both.
- Translate ambiguous business requirements into actionable insights with an emphasis on accuracy.
- Manage business analytic projects through all phases, including data quality, data modelling, algorithm/target development, statistical analysis, data visualisation, and presentation of results and deliverables.
- Core technical contributor building models and intelligence layers that power AI agents, insights engines, and GenAI enhanced platforms.
- Developing and building ML models (e.g., forecasting, anomaly detection, attribution, causal inference) used by AI agents and insights platforms.
- Building RCA and recommendation engines that enhance summarisation and chatbot capabilities.
- Keep up-to-date with the latest industry trends and technologies to ensure work remains pioneering.
Minimum Qualifications
Minimum years of Data Visualisation, Data Science, Data Analysis, or Data Translation role, with a keen eye for design and attention to detail.
Programming skills in Python and SQL, and experience with AWS, Snowflake, Spark, and Tableau.
Strong data analysis skills to conduct deep dives by applying statistics and machine learning to generate clear actionable insights.
Exceptional communication skills, with the ability to communicate complex analyses clearly to executive leadership and technical and non-technical audiences.
Demonstrated experience collaborating closely with business teams to deep dive into business performance and improve reporting dashboards on key operational metrics.
Experience applying GenAI and LLMs to real-world data analytics problems including RAG architectures, and LLM prompt evaluation.
Preferred Qualifications
Deep understanding of statistical modelling and causal inference, including experimental and observational analysis, hypothesis testing, and measurement design.
Demonstrated ability to collaborate with business analysts to design A/B tests to demonstrate effectiveness.
Comfortable with a variety of data stores such as Snowflake, familiar with distributed analytics engines.
Develop reusable models and data products working closely with Data Engineers to ensure scalability of models and products in production.
Familiarity with database modelling and data warehousing principles and comfortability working with modern data technologies.
Experience articulating and translating business questions into data solutions and proven ability to lead development projects from start to finish.
Able to balance competing priorities, long-term projects, and ad hoc requirements.
Demonstrated ability to positively influence and collaborate with people across all functional areas of an organisation.
Demonstrated ability to achieve strategic goals in an innovative and fast-paced environment.
Outstanding ability to problem solve, develop creative solutions, and demonstrate resourcefulness, while maintaining extreme attention to detail.
An eagerness and ability to learn new skills and solve dynamic problems in an encouraging and expansive environment.
Excellent communication skills, able to inspire non-technical colleagues on value proposition and impact of data.