Job Description
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Company Overview
A leading global software technology organization is seeking an experienced data science professional to support its Go-To-Market (GTM) Data Science and Analytics function. The organization develops digital products and services used by customers worldwide and leverages data, analytics, and technology to drive business growth and improve customer experiences.
The role focuses on applying advanced data science and analytics to the full customer journey, including acquisition, conversion, engagement, monetization, retention, and churn. The successful candidate will work closely with strategy, product, marketing, and finance teams to identify growth opportunities, explain business performance, and translate complex data into actionable recommendations.
The Opportunity
The organization is seeking an experienced Senior Data Scientist, GTM Data Science to help develop growth strategies for its B2C digital business. The role will apply data science to key stages of the customer journey and use analytical insights to influence business strategy and decision-making.
Key Responsibilities
- Analyze customer behavior across the end-to-end funnel to identify factors influencing acquisition, conversion, retention, and churn.
- Conduct exploratory data analysis to uncover patterns and trends throughout the customer lifecycle.
- Investigate anomalies within the customer funnel and determine whether performance changes are driven by market trends, product changes, or technical friction.
- Support Run-the-Business (RTB) activities by analyzing weekly performance across the GTM funnel and identifying key drivers of acquisition and retention.
- Communicate analytical insights clearly to senior leaders by translating complex findings into concise, decision-ready narratives.
- Partner with teams across GTM Strategy, Product, Marketing, and Finance to identify and evaluate growth opportunities.
- Apply data science and statistical techniques to solve complex business problems and improve decision-making.
- Contribute to shared code libraries and help establish technical best practices across the data science team.
- Peer-review complex analytical work to maintain a high technical standard.
- Partner with Data Engineering teams to optimize data architecture for high-velocity analytics.
- Drive projects independently from problem definition through analysis, recommendations, and business impact.
Required Qualifications
- 5+ years of experience in data science, analytics, experimentation, applied statistics, or a related field.
- Experience in a B2C SaaS, subscription, e-commerce, digital product, or similar environment is preferred.
- Strong SQL and Python skills.
- Experience working with large-scale datasets in modern data environments such as Databricks, Spark, or similar platforms.
- Strong foundation in statistics and quantitative methods.
- Experience with regression, hypothesis testing, forecasting, experimentation, causal inference, predictive modeling, or related analytical techniques.
- Demonstrated experience using data to solve business problems in collaboration with non-technical stakeholders.
- Ability to work independently in ambiguous environments and prioritize competing objectives effectively.
- Proven ability to drive projects from problem definition through recommendations and implementation.
- Experience with data visualization tools such as Tableau or Power BI.
- Strong communication skills with the ability to present complex analytical findings to senior leadership.
- Master’s degree in Statistics, Computer Science, Economics, Mathematics, another quantitative field, or equivalent professional experience.
Preferred Qualifications
- Experience analyzing customer lifecycle, acquisition, conversion, retention, and churn.
- Experience working with subscription or digital product business models.
- Experience conducting experimentation and causal analysis.
- Experience building scalable analytical solutions using modern data platforms.
- Experience collaborating with Data Engineering teams on data architecture and analytics infrastructure.
- Strong business acumen and the ability to connect analytical findings to strategic decisions.
- Experience mentoring peers or contributing to the technical development of a data science team.
Disclaimer
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- No Client Relationship: This company is not a client of SpringCube unless stated.
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