About the role
AI summarisedApple is seeking a senior data scientist for its Channel Sales organisation in ANZSA to design and implement AI-powered analytical solutions that support regional sales growth. The role involves bridging data science and business by collaborating with cross-functional teams to develop, productionalise, and validate advanced ML and AI models, including LLMs, GNNs, and RLHF, applied to business problems like pricing, coverage, and competitive landscape. The ideal candidate will have strong technical expertise in Python, SQL, and ML libraries, along with exceptional communication and leadership skills to influence stakeholders and drive data-driven decision-making.
TechnologyOnsiteSales and Business Development
Key Responsibilities
- Collaborate with business leaders and cross-functional stakeholders to proactively identify business opportunities
- Translate complex business problems into well-defined analytical requirements
- Perform exploratory data analysis (EDA) and formulate hypothesis to uncover business opportunities or challenges
- Design and deploy statistical models to simulate potential outcomes for critical business topics such as affordability, coverage, competitive landscape, and price elasticity
- Develop solutions that turn data into insights by leveraging state-of-the-art techniques ranging from ML optimisation to RLHF, GNN, and Generative AI
- Partner with engineering teams to productionalise models and solutions
- Define and implement robust validation strategies to ensure model accuracy, reliability, and generalisability using quantitative and qualitative insights
- Collaborate with data engineering teams to build and maintain robust data pipelines and deploy high-performance scalable models in production
- Collaborate closely with Worldwide (WW) teams to localise global AI tools and emerging solutions for effectiveness and relevance within ANZSA
- Keep up-to-date with the latest industry trends and technologies to ensure work remains cutting-edge and propose continuous improvement of AI platforms
Requirements
- 8+ years of professional experience in ML, AI, Data Science, or related fields
- Proven track record of delivering impactful ML solutions in industry settings
- Advanced degree in Computer Science, Data Science, or a related field, or equivalent professional experience
- Track record of collaborating with distributed engineering or data science teams to deliver business value
- Deep understanding of ML principles including supervised/unsupervised learning and deep learning
- Specific expertise in advanced techniques such as RLHF, GNNs, or GenAI
- Expert proficiency in Python and standard ML libraries (e.g. PyTorch, Tensorflow) with experience writing clean, production-grade code
- Strong ability to write complex SQL queries to extract, transform, and analyze large datasets from relational databases
- Extensive command of statistical modeling and causal inference including measurement science, experimental design, and hypothesis testing
- Ability to translate complex data into clear, actionable recommendations for business growth
- Exceptional communication and leadership skills
- Proven ability to translate undefined business questions into end-to-end data solutions
- Articulate complex analyses clearly to executive stakeholders
- Demonstrated experience collaborating closely with business teams to deep dive into business performance and translate into solutions
- Demonstrated strengths in building and managing relationships with the ability to influence at all levels, both within an organisation and externally