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

Note: The job is a remote job and is open to candidates in USA. Lorven Technologies Inc. is seeking a Lead Data Scientist specializing in Propensity & Segmentation within the Telecom sector. The role involves building and deploying machine learning models while evaluating their effectiveness using business-centric metrics, all within a remote work environment.ResponsibilitiesBachelor's degree or Masters Degree in Computer science, or a related field, with minimum 10+ Years of relevant experienceYou should have at least 5+ years of professional experience as an applied Data Scientist building and deploying supervised and unsupervised machine learning modelsMust have Core DS Fundamentals: Deep understanding of traditional ML theory, including class imbalance mitigation, feature selection, probability calibration, and experimental designBusiness-Centric Evaluation: Ability to evaluate models beyond standard AUC/ROC, focusing on lift charts, precision-recall curves, tier separation, and financial ROIMust have Python Ecosystem: Advanced proficiency in Python, specifically utilizing the traditional data science stack (pandas, NumPy, scikit-learn, XGBoost, LightGBM) within notebook and script-based workflowsTelecom 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, wire centers, or census tractsAdvanced Cloud SQL & Tuning: Expert-level SQL proficiency on cloud data warehouses (BigQuery, Snowflake, or Redshift). You must know how to diagnose and fix poorly performing queries, optimize complex window functions, and handle heavy aggregations on tens of millions of rows efficientlyMemory Optimization: Practical experience handling datasets that exceed local memory constraints using batching, sampling, or large-scale data frameworks (e.g., PySpark, Dask, or warehouse-native tools like BigQuery ML/Snowpark)Strong analytical and problem-solving skills, with a proven track record of identifying and resolving complex billing issuesExcellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiencesSkillsBachelor's degree or Masters Degree in Computer science, or a related field, with minimum 10+ Years of relevant experienceAt least 5+ years of professional experience as an applied Data Scientist building and deploying supervised and unsupervised machine learning modelsCore DS Fundamentals: Deep understanding of traditional ML theory, including class imbalance mitigation, feature selection, probability calibration, and experimental designBusiness-Centric Evaluation: Ability to evaluate models beyond standard AUC/ROC, focusing on lift charts, precision-recall curves, tier separation, and financial ROIMust have Python Ecosystem: Advanced proficiency in Python, specifically utilizing the traditional data science stack (pandas, NumPy, scikit-learn, XGBoost, LightGBM) within notebook and script-based workflowsTelecom 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, wire centers, or census tractsAdvanced Cloud SQL & Tuning: Expert-level SQL proficiency on cloud data warehouses (BigQuery, Snowflake, or Redshift). You must know how to diagnose and fix poorly performing queries, optimize complex window functions, and handle heavy aggregations on tens of millions of rows efficientlyMemory Optimization: Practical experience handling datasets that exceed local memory constraints using batching, sampling, or large-scale data frameworks (e.g., PySpark, Dask, or warehouse-native tools like BigQuery ML/Snowpark)Strong analytical and problem-solving skills, with a proven track record of identifying and resolving complex billing issuesExcellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiencesCompany OverviewLorven Technologies, Inc. is a highly recognized provider of professional technology consultancy in the US. It was founded in 2001, and is headquartered in Plainsboro, New Jersey, USA, with a workforce of 1001-5000 employees. Its website is http://lorventech.com.Company H1B SponsorshipLorven Technologies Inc. has a track record of offering H1B sponsorships, with 1 in 2026, 11 in 2025, 11 in 2024, 13 in 2023, 14 in 2022, 12 in 2021, 17 in 2020. Please note that this does not guarantee sponsorship for this specific role.