Staff Data Scientist

Intuit's Global Business Solutions Group seeks an experienced Staff Data Scientist to play a key role in scaling data-powered services by constructing and standardizing customer profiles. You will customize existing models as needed and build new models to organize structured and unstructured data, produce customer insights, and recommend segmentation strategies to maximize the value of unique data. This data will power experiences for customers both within products and extending beyond the product ecosystem.

In this role, you will collaborate with a highly cross-functional team, Including product, data, and AI teams, business development leaders, and strategy leaders. You will leverage your strong statistical, machine learning, NLP, and ETL skills to transform data into actionable insights that drive monetization use cases such as Intuit SMB MediaLabs, a first-of-its-kind B2B media network focused solely on small businesses powered by the unmatched 1st party business data of Intuit. If you have a proven track record of delivering impactful data science solutions and influencing stakeholders, we are waiting for you to join us and do the best work of your life.

Responsibilities

• Support developing a comprehensive multi-year vision for customer profiling and monetization that aligns with the product strategy and data infrastructure, ensuring the timely delivery of MVPs for immediate business needs.
• Analyze extensive behavioral data to develop comprehensive customer profiles, identifying behaviors and needs through deterministic signals and probabilistic inferences. Translate these insights into actionable recommendations that align with strategic business objectives.
• Utilize data mining, machine learning, and NLP techniques on our extensive SMB datasets to derive deep insights and drive impactful business solutions.
• Conduct hands-on data analysis and modeling, including ETL processes, data cleaning, and data preparation for modeling.
• Lead complex analytics requirements conversations on strategic projects, serving as a thought partner to stakeholders in scoping, prioritizing, and guiding key decisions.
• Build scalable data processes and robust data products by anticipating future business challenges and designing effective methodologies and solutions.
• Maintain data integrity, confidentiality, and availability by strictly adhering to data stewardship principles and guidelines.