Senior Data Scientist - Go-To-Market (GTM)

Position Overview:

We are seeking a highly analytical and impact-driven Senior Data Scientist to enhance our Go-To-Market strategies through data-driven insights. In this role, you will focus on optimizing sales, support, or marketing efforts, analyzing customer acquisition channels, and identifying opportunities to drive revenue growth. You will collaborate closely with cross-functional teams, including Sales, Marketing, Finance, and Product, to inform and refine our GTM approach.

What You’ll Do:

• Analyze GTM Performance and evaluate the effectiveness of various sales and marketing channels, campaigns, and initiatives to identify key drivers of customer acquisition and retention.
• Create models to forecast sales trends, customer lifetime value, and churn, enabling proactive adjustments to GTM strategies.
• Develop and utilize clustering and segmentation techniques to identify distinct customer groups, tailoring GTM strategies to each segment.
• Work closely with Sales, Marketing, Finance, and Product teams to provide data-driven recommendations that enhance lead generation, conversion rates, and overall revenue.
• Analyze pricing strategies and product offerings to determine optimal configurations that maximize market penetration and profitability.
• Design and implement experiments to test the impact of different GTM tactics, ensuring continuous improvement and learning.
• Develop and maintain dashboards that track key GTM metrics, providing transparency and actionable insights to stakeholders.
  

What You Bring:

• Experience in GTM Analytics or similar role, with a proven track record in analyzing and optimizing sales and marketing strategies, preferably in a SaaS environment.
• Expertise in translating complex data into insights that are actionable for cross-functional teams.
• Proficiency with data analytics tools and platforms (e.g., Looker, Amplitude) is a plus but not required. A focus on solving product challenges is more important than specific tool experience.
• Experience in building and maintaining reliable analytics infrastructures.
• Excellent communication skills, with the ability to clearly present data insights to both technical and non-technical stakeholders.
• Experience with 0 to 1 product initiatives is a plus, though not required.
• A high level of accountability, a passion for continuous learning, and the ability to thrive in a fast-paced, dynamic environment.

Qualifications:

• Degree in Analytics, Applied Mathematics, Economics, Statistics, or related analytical field of study, or an equivalent combination of training and experience.
• Deep experience in working with exploratory analysis projects related to cohorting, time series analysis, and funnel analysis/optimization is required.
• Expert-level proficiency in influencing product strategy with SQL, A/B testing, machine learning, statistical analysis, and related tools like R, Python, SAS, etc., is required.
• Previous or current experience supporting SaaS (Product-Led Growth) companies with uncovering gaps and recalibrating activation metrics (e.g., aha/habit moments) is a huge plus.
• Proven ability to thrive in a fast-paced, dynamic startup environment with a high level of adaptability and a strong product sense, ensuring insights align with customer needs and product goals.