Staff Data Scientist

Key Skills

Algorithms, Data Analysis, Data science techniques, Design, Natural Language Processing (NLP), Python Programming, R Programming, SQL

Job Description

Intuit’s Small Business Group (SBG), serves the needs of small businesses and self-employed through Quickbooks and our ecosystem of attached products. Our mission is to power prosperity around the world, which means dramatically rethinking how we enable small businesses and individuals to run their businesses with confidence.

The Data team is searching for a talented Staff Data Scientist to drive initiatives across the Australia and Rest-of-World (AUROW) Business. We are an exciting, fast paced, and innovative team, leveraging industry-leading tools and best practices.

As a Staff Data Scientist, you will collaborate with cross functional teams to develop insights, lead experimentation, develop ML models, and drive key business results. You will take complex concepts and communicate them to both technical and non-technical leaders in order to effect change for our customers. You will be an instrumental leader in shaping the strategy and future of the AUROW Data Science Program, particularly focused on Product AI. Working across Intuit AI, Data Engineering, Product, Marketing and Sales you will support an integrated plan to grow and scale Data Science for the SBG business.

Qualifications

• Advanced in SQL and a statistical programming language such as Python and/or R
• 5+ years experience in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, anomaly detection, recommender systems, sequential pattern discovery, and text mining
• Expertise in experimental design and Multivariate/A-B testing
• Willingness and ability to adapt to rapid business and organizational changes that accompany a high-growth environment
• Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.
• Undergraduate Degree in Quantitative Field, or equivalent experience

Responsibilities

• Perform hands-on data analysis and modeling with large data sets
• Lead experimental designs and measurement plans
• Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms
• Work side-by-side with product managers, software engineers, and designers in designing models, experiments, and minimum viable products
• Explore new design or technology shifts in order to determine how they might connect with the customer benefits we wish to deliver