Intuit's Global Business Solutions Group (GBSG) GTM Analytics team is looking to accelerate growth in the Mid Market organization by enhancing customer segmentation, optimizing targeting strategies, and improving demand generation effectiveness across acquisition, conversion, and retention.
Requirements
- Advanced skills in SQL and Python (or R) for data extraction, modeling, and analysis.
- Proficiency with data visualization platforms to communicate insights clearly; strong preference for Tableau.
- Proven track record applying segmentation, targeting, and experimentation to drive acquisition, conversion, and retention improvements.
- Experience analyzing demand generation, funnel performance, and marketing/sales effectiveness.
Responsibilities
- Develop and refine advanced segmentation frameworks to identify, prioritize, and engage high-value Mid Market customers.
- Build predictive models (e.g., propensity, churn, LTV) to inform targeting strategies across sales and marketing channels.
- Analyze the full GTM funnel to identify drivers of acquisition, conversion, and retention.
- Provide insights into marketing campaign performance, sales pipeline health, and channel effectiveness to maximize ROI.
- Design and execute experiments to test GTM hypotheses, validate strategies, and optimize initiatives.
- Apply causal inference methods to measure the true impact of marketing and sales efforts.
- Build measurement frameworks that provide visibility into acquisition, conversion, and retention outcomes.
Other
- 4+ years of experience in data science, analytics, or related quantitative fields, ideally in GTM, marketing analytics, or growth-focused roles.
- Strong communication and storytelling skills with experience influencing business and technical stakeholders.
- Ability to quickly understand new business areas and translate complex analyses into actionable strategies.
- Customer-obsessed, with a passion for uncovering insights that improve acquisition, conversion, and retention.
- Agile and pragmatic, balancing rigorous analysis with fast, iterative execution.
- Bachelor’s degree in a quantitative discipline (Data Science, Statistics, Mathematics, Economics, Computer Science, or Engineering); Master’s preferred.
