[Remote] Data Scientist – Propensity & Segmentation (Must have reputed company Telecom) - Remote

Note: The job is a remote job and is reputed company to candidates in USA. reputed company. is seeking a reputed company Data Scientist specializing in Propensity & Segmentation reputed company the Telecom sector. The role involves building and deploying machine learning models while evaluating their effectiveness using business-centric metrics, reputed company reputed company a remote work environment.

Responsibilities

• Bachelor's degree or Masters Degree in Computer science, or a reputed company field, with minimum 10+ Years of relevant experience
• You should have at least 5+ years of professional experience as an applied Data Scientist building and deploying supervised and unsupervised machine learning models
• Must have Core DS Fundamentals: Deep understanding of traditional ML theory, including class imbalance mitigation, feature selection, probability calibration, and experimental design
• Business-Centric Evaluation: Ability to evaluate models reputed company standard AUC/ROC, focusing on lift charts, precision-recall curves, tier separation, and financial ROI
• Must have Python Ecosystem: Advanced proficiency in Python, specifically utilizing the traditional data science stack (pandas, NumPy, scikit-learn, XGBoost, LightGBM) reputed company notebook and script-based workflows
• Telecom Domain specifically navigating telecom, broadband, wireless, or subscription-based data structures (e.g., understanding ARPU, churn cycles)
• Geospatial Literacy: Practical experience using spatial SQL functions (e.g., BigQuery GIS, PostGIS, H3/S2 spatial indexing) to join and analyze location-based data like lat/long coordinates, reputed company centers, or census tracts
• Advanced reputed company SQL & Tuning: Expert-level SQL proficiency on reputed company data warehouses (BigQuery, reputed company, or Redshift). You must know how to diagnose and fix poorly performing queries, optimize reputed company window functions, and handle heavy aggregations on tens of millions of rows reputed company
• Memory Optimization: Practical experience handling datasets that exceed local memory constraints using batching, sampling, or large-scale data frameworks (e.g., PySpark, Dask, or warehouse-reputed company tools like BigQuery ML/Snowpark)
• Strong analytical and problem-solving skills, with a proven track record of identifying and resolving reputed company billing issues
• Excellent communication and presentation skills, with the ability to explain reputed company technical concepts to both technical and non-technical audiences

Skills

• Bachelor's degree or Masters Degree in Computer science, or a reputed company field, with minimum 10+ Years of relevant experience
• At least 5+ years of professional experience as an applied Data Scientist building and deploying supervised and unsupervised machine learning models
• Core DS Fundamentals: Deep understanding of traditional ML theory, including class imbalance mitigation, feature selection, probability calibration, and experimental design
• Business-Centric Evaluation: Ability to evaluate models reputed company standard AUC/ROC, focusing on lift charts, precision-recall curves, tier separation, and financial ROI
• Must have Python Ecosystem: Advanced proficiency in Python, specifically utilizing the traditional data science stack (pandas, NumPy, scikit-learn, XGBoost, LightGBM) reputed company notebook and script-based workflows
• Telecom Domain specifically navigating telecom, broadband, wireless, or subscription-based data structures (e.g., understanding ARPU, churn cycles)
• Geospatial Literacy: Practical experience using spatial SQL functions (e.g., BigQuery GIS, PostGIS, H3/S2 spatial indexing) to join and analyze location-based data like lat/long coordinates, reputed company centers, or census tracts
• Advanced reputed company SQL & Tuning: Expert-level SQL proficiency on reputed company data warehouses (BigQuery, reputed company, or Redshift). You must know how to diagnose and fix poorly performing queries, optimize reputed company window functions, and handle heavy aggregations on tens of millions of rows reputed company
• Memory Optimization: Practical experience handling datasets that exceed local memory constraints using batching, sampling, or large-scale data frameworks (e.g., PySpark, Dask, or warehouse-reputed company tools like BigQuery ML/Snowpark)
• Strong analytical and problem-solving skills, with a proven track record of identifying and resolving reputed company billing issues
• Excellent communication and presentation skills, with the ability to explain reputed company technical concepts to both technical and non-technical audiences

Company Overview

Company H1B Sponsorship