Data Scientist

About the Company We are a recruiting for a leading company in the telecom industry, dedicated to providing innovative solutions and exceptional service to our customers. Our mission is to leverage data and technology to enhance connectivity and improve user experiences. We foster a culture of collaboration, inclusivity, and continuous learning. About the Role The Lead Data Scientist – Propensity & Segmentation will play a crucial role in analyzing telecom data to drive business decisions and strategies. This position requires a deep understanding of data science principles and the ability to apply them in a practical, business-focused manner. Responsibilities • 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. • Advanced 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 efficiently. • 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-native tools like BigQuery ML/Snowpark). • Experience: 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 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. Qualifications Education details: A degree in Data Science, Computer Science, Statistics, or a related field is preferred. Required Skills • Expert-level SQL proficiency on cloud data warehouses. • Practical experience with large-scale data frameworks. • Advanced proficiency in Python and data science libraries. Preferred Skills • Experience with geospatial data analysis. • Knowledge of machine learning model evaluation techniques. Pay range and compensation package arounf $60/hr (open to C2C) (based on experience level) Equal Opportunity Statement We are committed to creating a diverse and inclusive workplace. We welcome applicants from all backgrounds and experiences to apply.