Hi,
Please review the below job requirement and let me know if you are good to submit with the below details filled and your latest resume ASAP.
Job Title: Lead Data Scientist – Propensity & Segmentation (Telecom)
Location: Irving TX-Onsite
ROLE SUMMARY
We build the propensity models and customer segmentation frameworks that drive how we target, acquire, and retain millions of households. This is a 100% hands-on role for a seasoned Data Scientist who loves digging into data and owning execution from end to end. We are looking for someone who can write highly optimized, large-scale SQL feature queries, apply rigorous traditional machine learning methods (avoiding rookie pitfalls like data leakage or uncalibrated models), and turn raw data into high-value targeting lists for marketing.
If you are a practitioner who thrives on optimizing data pipelines, mastering telecom data structures, and applying core data science principles to large-scale datasets, this role is for you.
REQUIRED MACHINE LEARNING & EXPERIENCE
Experience: 15+ 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 beyond standard AUC/ROC, focusing on lift charts, precision-recall curves, tier separation, and financial ROI.
Python Ecosystem: Advanced proficiency in Python, specifically utilizing the traditional data science stack (pandas, NumPy, scikit-learn, XGBoost, LightGBM) within notebook and script-based workflows.
TELECOM & GEOSPATIAL REQUIREMENTS (MUST HAVE)
Telecom Domain Expertise: 3+ years 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 tracts.

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Lead Data Scientist – Propensity & Segmentation (Telecom)

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