Staff Data Scientist, Expert Network

Intuit • Mountain View, CA • 2h ago

Overview

Join the Intuit Customer Success team as a Staff Data Scientist focused on our Expert Network. In this role, you will help shape the AI strategy for our product support and live experiences. You'll be central to optimizing our greatest resource-our people-through innovating, experimenting, learning, pivoting, and scaling AI-driven solutions.

As a Staff Data Scientist, you will join our team of talented Data Engineers, Data Analysts, and Data Scientists to develop tools, define metrics, and build a robust Data/AI infrastructure that informs critical business decisions. You will also partner closely with cross functional teams in AI Research, Product Management, Service Delivery, Strategy, and Engineering to develop capabilities that will drive our AI Driven platform into the future.

Responsibilities

Perform hands-on data analysis and modeling to enable insight and scale the application of AI on large datasets.

Lead experimental designs and measurement plans.

Apply data mining, NLP, and machine learning (both supervised and unsupervised) to improve relevance and personalization algorithms.

Build optimization models and simulation tools to support strategic decisions across customer success operations, including workforce planning, customer escalations, root cause analysis, scheduling, and routing.

Develop and operationalize decision science frameworks to optimize support costs and maximize customer outcomes.

Partner with stakeholders across Customer Success, Operations, and Strategy teams to embed AI/ML solutions in real-time decision engines and operational workflows.

Work side-by-side with product managers, software engineers, and designers in designing models, experiments, and minimum viable products.

Develop generative AI capabilities to power our Expert Network and streamline processes, uncover insights, and reduce the manual burden on the team.

Qualifications

BS or MS degree in Statistics, Mathematics, Operations Research, Computer Science, Econometrics, or a related field.

Advanced proficiency in SQL and a statistical programming language such as Python and/or R.

7+ years of 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.

Deep understanding of Generative AI and other evolving technologies to accelerate insights from multi-modal data.

Expertise in experimental design and Multivariate/A-B testing.

Strong background in optimization techniques, such as linear programming, integer programming, constraint optimization, and simulation modeling.

Experience building and deploying operational models for staffing, queue management, or dynamic resource allocation.

Familiarity with customer success metrics and operational KPIs such as Net Promoter Score (NPS), Average Handle Time (AHT), First Contact Resolution (FCR), and agent utilization.

Ability to formulate data-backed strategies that will drive step-function growth for the business as well as increase customer benefit.

Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits (https://www.intuit.com/careers/benefits/full-time-employees/) ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:

EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.

Intuit

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