Intuit is hiring a Data Scientist 2 to join the Intuit AI Futures team.
In its intrapreneurial function, the AI Futures team develops and incubates emerging technologies, user experiences, capabilities, and products that have the potential to be transformative to businesses and consumers. We are seeking candidates who are experts in generative AI, deep learning, and have strong engineering skills. We work across Intuit products, looking for ways to turn state-of-the-art industry advancements into benefits for our customers. You will join a high-caliber team of data scientists and machine learning engineers to shape our strategy in this area and develop advanced capabilities that serve our customers' needs, both current and future.
ResponsibilitiesWork with a cross-functional team of designers, program managers, researchers, legal experts, and more, to create new capabilities for current and future products.Work with data scientists and machine learning engineers to create and refine features from the underlying data and build pipelines to train and deploy models.Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.Run regular A/B tests, gather data, perform statistical analysis, and draw conclusions on the impact of your models.Minimum RequirementsBS, MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.) or equivalent work experience.1+ years of experience in modern data science tools and proficient in Python and typical data science libraries (e.g., TensorFlow, PyTorch, Keras).Efficient in SQL.Comfortable in a Linux environment.1+ years of experience in machine learning techniques such as classification, regression, decision trees, neural nets, large language models, recommender systems, natural language processing, clustering, anomaly detection, sequential pattern discovery, text mining, and familiar with the latest trends and applications of generative AI.Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.
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