Senior Data Scientist, Customer Analytics

Autodesk•AMER - United States - Oregon - Offsite/Home, OR

3d•$112,000 - $200,860

About The Position

We are looking for a Senior Data Scientist to join our Customer Analytics team, with a strong focus on predictive analytics across product usage and customer lifecycle. In this role, you will develop models and insights to understand user behavior, predict churn and expansion, and drive strategies that improve product adoption and customer outcomes. You will also bring familiarity with emerging AI techniques to enhance analytical approaches and unlock additional value from data. You will work closely with Customer Success, Product, and Go-to-Market teams to turn data into actionable recommendations.

Requirements

5–7+ years of experience in Data Science, Advanced Analytics, or similar roles
Strong proficiency in Python (preferred) or R for data analysis and modeling
Hands-on experience with predictive modeling techniques (e.g., regression, classification, clustering)
Strong SQL skills and experience working with large-scale datasets
Solid understanding of customer analytics concepts (churn modeling, segmentation, cohort analysis)
Working knowledge of machine learning/AI techniques and when to apply them to business problems
Strong analytical thinking and problem-solving skills with a focus on business impact
Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or related field

Nice To Haves

Experience working with product usage / telemetry data
Experience in SaaS or subscription-based business models
Familiarity with customer lifecycle metrics (retention, LTV, engagement)
Exposure to AI applications such as NLP, recommendation systems, or unstructured data analysis
Experience with data visualization tools (Tableau, Power BI)
Strong stakeholder management and communication skills

Responsibilities

Analyze product usage data to identify behavioral patterns, segmentation opportunities, and growth drivers
Develop predictive models to analyze customer churn, retention, expansion, and product adoption
Build customer health scores and predictive signals to support proactive customer success strategies
Apply appropriate AI/ML techniques (e.g., advanced segmentation, pattern detection, NLP where relevant) to enhance insights
Translate business questions into analytical frameworks and data science solutions
Partner with Customer Success and Product teams to identify opportunities to improve engagement and reduce churn
Generate actionable insights and recommendations to influence business decisions
Communicate complex analyses clearly to both technical and non-technical stakeholders
Collaborate with BI teams to embed predictive insights into dashboards and reporting