What are the responsibilities and job description for the Decision Science Analytics position at Inherent Technologies?
Position: Decision Science Analytics
Location: San Antonio, TX ***Onsite***
Duration: 2 Years
Must have skill: Python, Streamlit, SAS, SQL, Tableau, Predictive Modeling, A/B Testing, Customer Analytics & Retention Modeling
Job Description
Required Experience:
4 years in data science, advanced analytics, or a related quantitative role focusing on customer behavior.
Domain Knowledge: Strong understanding of customer lifecycle metrics, loyalty programs, and retention strategies. Education: Bachelor's or Master's degree in Statistics, Economics, Computer Science, Mathematics, or a related field.
Responsibilities
Predictive Modeling: Build machine learning models to forecast customer churn and identify cross-sell or upsell opportunities.
Customer Segmentation: Analyze behavior patterns to group customers and target them with personalized retention campaigns.
Experimentation: Design and execute A/B tests to measure the impact of retention and deepening initiatives.
Data Storytelling: Translate complex data insights into clear recommendations for marketing and product teams.
Performance Tracking: Build dashboards and reports to monitor key retention metrics like churn rate, retention rate, and lifetime value.
Qualifications Languages
Advanced proficiency in Python and SAS for advanced analytics and predictive modeling.
Database: Strong expertise in SQL for complex data extraction, manipulation, and pipeline creation.
Visualization: Expert-level skills in Tableau to build interactive dashboards and track customer metrics.
Location: San Antonio, TX ***Onsite***
Duration: 2 Years
Must have skill: Python, Streamlit, SAS, SQL, Tableau, Predictive Modeling, A/B Testing, Customer Analytics & Retention Modeling
Job Description
Required Experience:
4 years in data science, advanced analytics, or a related quantitative role focusing on customer behavior.
Domain Knowledge: Strong understanding of customer lifecycle metrics, loyalty programs, and retention strategies. Education: Bachelor's or Master's degree in Statistics, Economics, Computer Science, Mathematics, or a related field.
Responsibilities
Predictive Modeling: Build machine learning models to forecast customer churn and identify cross-sell or upsell opportunities.
Customer Segmentation: Analyze behavior patterns to group customers and target them with personalized retention campaigns.
Experimentation: Design and execute A/B tests to measure the impact of retention and deepening initiatives.
Data Storytelling: Translate complex data insights into clear recommendations for marketing and product teams.
Performance Tracking: Build dashboards and reports to monitor key retention metrics like churn rate, retention rate, and lifetime value.
Qualifications Languages
Advanced proficiency in Python and SAS for advanced analytics and predictive modeling.
Database: Strong expertise in SQL for complex data extraction, manipulation, and pipeline creation.
Visualization: Expert-level skills in Tableau to build interactive dashboards and track customer metrics.