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Senior Staff Data Scientist, Marketing

Category Data Location Toronto, Canada Job ID 2025-70147
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Company Overview

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

Intuit is seeking a visionary and results-driven Senior Staff Data Scientist to drive  data, advanced analytics and AI-driven insights to optimize marketing and direct channel performance and drive significant business growth. This role is pivotal in shaping the future of QuickBooks and Mailchimp marketing, ensuring data-driven decision-making across all channels and initiatives.

As a key member of our Data Science and Analytics team, you will be responsible for developing and implementing cutting-edge methodologies to measure marketing effectiveness, predict customer behavior, develop AI-driven insights, and build predictive and behaviour-based models to optimize conversion rates and optimize marketing spend. 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 our products, working across Intuit AI, Data Engineering, and Marketing to grow and scale the Canadian Go-To-Market Roadmap. You will be a strategic partner to the marketing leadership team, providing actionable insights that fuel growth and innovation.

Please note that this role will be working on a hybrid model of 3x per week on site in our Toronto office.

Responsibilities

  • Perform hands-on data analysis, derive insights, tell stories with data, educate effectively, instill confidence in recommendations, and motivate others to act
  • Guides cross-functional teams to new data sets, customer insights or methodological approaches to accelerate and improve the AI models outcomes
  • Support the development and maintenance of ML/AI models and other personalization algorithms
  • Drive an iterative experimentation culture by combining quantitative insights, strategic thinking and qualitative learnings that increase learning and success rate.
  • Understand multiple Causal Inference methods (Propensity Score, DiD, Synthetic Control, etc..) and when to use them to answer key business questions.
  • Use data, strategic thinking and advanced scientific methods including predictive modeling to enable data-backed decision making for Intuit at scale
  • Partner with marketing managers, software engineers and data team  in designing experiments and developing minimum viable products
  • Run regular A/B tests, gather data, perform statistical analysis, draw conclusions and communicate results to peers and leader
  • Design and implement a measurement framework and high impact learning agenda drive increased marketing effectiveness
  • Able to identify key patterns on customer behavior by connecting insights across a portfolio of experiments and analysis done across the Business Unit
  • Lead the media mixed modeling process- we are in the process of moving our MMM from agency to in-house, you will play the lead role in this process, with model selection, model build / training and responsibility for actioning the model outputs with the marketing team
  • Work with the marketing leadership, finance, research, product, and data teams to build marketing KPIs and goals
  • Assist the marketing leadership team with prioritizing, assigning, and understanding the impact of programs, campaigns, and marketing investments
  • Continuous communication of overall marketing performance to marketing leadership team and cross-functional stakeholders
  • Strong ability to analyze quantitative data and provide actionable recommendations
  • Stay abreast of industry trends, emerging technologies, and advancements in marketing analytics to ensure our strategies remain cutting-edge
  • Present findings and recommendations to senior leadership- effectively communicating complex data in a clear and concise manner

Qualifications

  • 7-8 years of experience working in marketing, web, or other related analytics and data science fields
  • Highly proficient in SQL, Tableau, Qlik, and Google Sheets
  • Experience with programming languages including R or Python
  • Excellent problem-solving skills and end to end quantitative thinking
  • Statistical knowledge to guide and support A/B testing or other experimentation frameworks, and interpret the results to draw detailed and practical conclusions
  • Ability to manage through ambiguity in a high paced growth environment
  • Ability to manage E2E aspects of a complex analytics model/project build (i.e., scope, requirements gathering/finalizing, stakeholder management, communication, project management) that drives BU decision making.
  • Great communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences
  • Strong proficiency in marketing analytics tools and technologies, such as Google Analytics, Adobe Analytics, and marketing automation platforms
  • Strong proficiency in data tools such as Databricks
  • Advanced analytics techniques: expertise in regression models (e.g. ridge regression, Bayesian regression), time series analysis, forecasting + end to end MMM ownership experience
  • Excellent leadership and project management skills, with the ability to work effectively with cross-functional teams and manage multiple projects simultaneously
  • Solid modeling foundation is essential, including hands-on expertise with data mining and statistical modeling techniques such as clustering, classification, regression, tree-based methods, neural nets, support vector machines, anomaly detection, and natural language processing.
  • Great communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences
  • Bachelor's degree in Computer Science, Statistics, Economics, Mathematics, Data Analytics, Finance, Advanced Analytics preferred or equivalent work experience
  • Ability to evaluate, coordinate, and prioritize requirements in a fast-paced environment
  • Experience in the technology space is preferred
  • Experience in a global organization is preferred
  • Advanced degree in statistics, economics, behavioral science is preferred
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