Description

• 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.
• Extract meaningful insights from data and effectively communicate findings to optimize churn prediction models using metrics like AUC and lift.
• 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.
• Develop software programs, algorithms, and automated processes to cleanse, integrate, and evaluate datasets for customer segmentation, ML model training and evaluation.
• Generate actionable insights and solutions by translating complex model outputs into business-friendly insights for targeted retention strategies.

Requirements

• Proficiency in Python & SQL - other languages a benefit.
• Bachelor's Degree in Computer Science, Data Analytics, Engineering, or a related field. Master’s and Ph.D. graduates welcome.
• Effective collaboration skills within a team environment.
• Demonstrated passion and aptitude for problem-solving.
• Minimum of 5 years of experience in data science, data engineering or a related field, with demonstrated expertise in building, evaluating, and deploying machine learning models for predictive analytics, particularly in areas like churn prediction.
• Strong critical thinking abilities and the capacity to work autonomously.
• Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools, coupled with strong statistical modeling skills for churn analysis and customer segmentation, including cohort analysis and the use of demographic and firmographic data.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance