Quantiphi is looking to understand, predict, and mitigate customer churn to improve customer lifetime value and overall business growth.
Requirements
- Expert-level SQL skills for querying and manipulating large datasets.
- Strong understanding and practical application of statistical modeling, hypothesis testing, regression analysis, time-series analysis, and various machine learning algorithms (e.g., Logistic Regression, Random Forests, Gradient Boosting, Survival Analysis) for predictive modeling.
- Advanced proficiency in Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn) or R for data manipulation, statistical analysis, and model development.
- Expertise in data visualization tools such as Tableau, Looker, Power BI, or similar platforms to create insightful dashboards and reports.
- Hands-on experience with GCP services, particularly BigQuery for data warehousing and analytics.
- Experience with other GCP services like Cloud Storage, Dataflow, or Vertex AI is a plus.
- Experience with MLOps practices for deploying and monitoring models.
Responsibilities
- Lead the end-to-end process of churn analysis, from data extraction and cleaning to model development and deployment.
- Develop and implement advanced statistical and machine learning models (e.g., survival analysis, classification models, time-series analysis) to predict customer churn with high accuracy.
- Identify and analyze key churn indicators, patterns, and segments across various customer touchpoints and product usage data.
- Conduct deep-dive analyses to uncover root causes of churn and identify actionable insights.
- Design, implement, and analyze A/B tests and experiments for various retention initiatives (e.g., personalized communications, feature adoption campaigns, win-back programs).
- Develop and maintain comprehensive dashboards and reports to track key churn and retention metrics, providing clear visibility into performance and trends.
- Leverage expertise in GCP (Google Cloud Platform) and BigQuery for efficient data extraction, transformation, and analysis.
Other
- 2+ years of progressive experience in data analysis, business intelligence, or data science roles, with a strong focus on customer churn analysis and retention strategies.
- Demonstrated ability to translate complex analytical findings into clear, actionable business recommendations that drive measurable results.
- Strong understanding of customer lifecycle management, customer segmentation, and key business metrics (e.g., LTV, CAC, ARPU).
- Experience in working on Churn analysis in Telco domain.
- GCP Professional Machine Learning Engineer certification.
