Über
Responsibilities
Provide Technical Leadership with hands on Data Science and Applied Research
Design, build, and own end‑to‑end ML solutions for SharedX surfaces, including personalization experiences for homepage, onboarding flows, dashboards, navigation, recommendations, and AI‑powered guidance.
Develop and iterate on ranking, recommendation, and personalization models that determine what content, actions, or insights are most relevant to customers.
Apply a broad ML and AI toolkit—supervised learning, deep learning, NLP and LLMs, and advanced ranking methods—to drive measurable improvements in customer outcomes.
Collaborate with platform and agent teams to incorporate models into conversational and agentic experiences that guide customers through multi‑step workflows.
Conduct deep data analysis, feature engineering, and model development using large‑scale behavioral and product datasets.
Partner with engineering to define data quality requirements and model‑ready pipelines.
Establish robust offline evaluation methods (relevance, calibration, fairness) and drive online experimentation strategy to validate impact.
Explore emerging techniques in LLM‑based personalization, planning, contextual bandits, and reinforcement learning, converting promising ideas into practical solutions.
Collaborate with product, engineering, design, and other scientists to shape ML priorities, define success metrics, and translate customer needs into technical solutions.
Provide strategic guidance on how machine learning and AI can improve onboarding, navigation, personalization, and multi‑surface customer journeys.
Mentor other scientists and engineers, elevating scientific rigor and best practices across SharedX.
Qualifications
Master’s or PhD in Computer Science, Statistics, Machine Learning, Applied Mathematics, or a related quantitative field, or comparable industry experience.
8+ years of experience building and deploying production ML systems end‑to‑end.
Expertise in core ML methodologies, applied statistics, experimentation, and personalization or recommendation systems.
Strong experience with Python, SQL, and ML frameworks such as PyTorch or TensorFlow.
Demonstrated ability to design, run, and interpret online experiments and apply insights to iterative product development.
Experienced in scientific exploration and shipping pragmatic, impactful solutions.
Communicate complex ideas clearly and work effectively across engineering, product, and design.
Responsible AI, customer trust, and creating experiences that feel intuitive, transparent, and genuinely helpful for small businesses.
Preferred Experience
Background in building or enhancing AI‑ or LLM‑powered product experiences, such as conversational assistants, intelligent workflows, or guided setup.
Experience with ranking and personalization challenges in multi‑surface product ecosystems.
Familiarity with causal inference, uplift modeling, or bandit‑based personalization.
Experience mentoring senior ICs and influencing cross‑functional stakeholders.
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). 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:
New York: $209,500 - $283,500
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Sprachkenntnisse
- English
Hinweis für Nutzer
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