Trimble is looking to leverage data to drive meaningful business outcomes and contribute to the success of Trimble's data-driven initiatives, particularly in understanding and improving customer retention for SketchUp
Requirements
- Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools
- Strong statistical modeling skills for churn analysis and customer segmentation, including cohort analysis and the use of demographic and firmographic data
- Proficiency in Python & SQL - other languages a benefit
- Demonstrated expertise in building, evaluating, and deploying machine learning models for predictive analytics, particularly in areas like churn prediction
- Experience with data science, data engineering or a related field
Responsibilities
- Design, develop, and program methods, processes, and systems to deploy ML models (e.g., logistic regression, XGBoost) to predict churn risk for SketchUp's diverse customer base
- Generate actionable insights and solutions by translating complex model outputs into business-friendly insights for targeted retention strategies
- Collaborate with product and go-to-market teams to engineer impactful features from raw customer data, developing metrics for tracking engagement and activity facilitating better understanding of customer behavior
- Develop software programs, algorithms, and automated processes to cleanse, integrate, and evaluate datasets for customer segmentation, ML model training and evaluation
- Extract meaningful insights from data and effectively communicate findings to optimize churn prediction models using metrics like AUC and lift
Other
- Bachelor's Degree in Computer Science, Data Analytics, Engineering, or a related field
- Minimum of 5 years of experience in data science, data engineering or a related field
- Strong critical thinking abilities and the capacity to work autonomously
- Effective collaboration skills within a team environment
- Ability to work in a hybrid role with a flexible work arrangement
