Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Job Overview
Come join the Intuit team as a Staff Data Science/MLEngineer.
Our Data Exchange group is responsible for acquiring millions of transactions and statements a day to satisfy our customers needs in all Intuit products.
You will utilize your skills to help develop and maintain machine learning models, using both analytical algorithms and deep learning approaches, that will be leveraged by critical backend systems of Intuits Data Acquisition Platform.
In this role, you will:
Lead and apply best practices in ML Project lifecycle management: scoping, data preparation, deployment, and monitoring
Collaborate with multiple teams at Intuit and contribute to components in different business units. We love engineers who lead the change, communicate with customers, and deliver the most beautiful and intuitive applications
Be expected to help architect, integrate, optimize, deploy, and code data pipelines and ML models at scale using the latest industry tools and techniques
#LI-Hybrid
Responsibilities
Design and build systems, which improve machine learning scalability, usability, and performance
Own end-to-end model development lifecycle, including defining problems, featurization in distributed process systems, model exploration, and development, deployment, and model performance monitoring
Collaborate with stakeholders to define success criteria and align model metrics with business goals
Work side-by-side with product managers, business analytics, data scientists, and backend engineers in enabling AI solutions for business use cases
Explore the state-of-the-art technologies and apply them to deliver customer benefits.
Roughly 50% hands-on coding
Requirements: 6+ years industry experience bringing AI models from modeling to production
Experience in modern, advanced analytical tools and programming
Expertise and experience in data mining algorithms and statistical modeling techniques such as classification, regression, clustering, anomaly detection, and text mining
Strong understanding of the Software design and architecture process
Experienced with working in cloud production-grade high-scale microservices environment
Languages such as Python, Java, or Scala
Expertise with Spark for data manipulation and featurization
Efficient in SQL, Hive, or SparkSQL
Comfortable in Linux environment
Familiar with backend services: K8S, Spring Boot, Vert.x, Docker
Excellent oral and written English communication skills: demonstrated ability to explain complex technical issues to both technical and non-technical audiences
BS, MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research), or equivalent work experience
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