Senior Data Scientist 5351

Key Responsibilities: Advanced Analytics & Data Science Develop and deploy scalable predictive and machine learning solutions that improve customer acquisition, retention, pricing strategies, and marketing performance. Own the end-to-end machine learning lifecycle, including model design, feature engineering, development, validation, deployment, monitoring, optimization, and continuous improvement to deliver accurate, reliable, and production-ready solutions. Apply advanced statistical techniques, machine learning, predictive analytics, and experimentation to solve complex business challenges, identify growth opportunities, and optimize business performance. Develop machine learning solutions using Big Query ML and Python libraries, including scikit-learn, XGBoost, LightGBM, and pandas. Communicate analytical insights and actionable business recommendations through compelling visualizations, dashboards, and executive-level presentations. Research, evaluate, and implement emerging AI and machine learning technologies to continuously enhance analytical capabilities and business outcomes. Data Engineering Develop robust SQL transformations and scalable data pipelines in Big Query. Build reusable datasets, feature stores, and automated model training and scoring pipelines. Implement model monitoring, performance tracking, and automated retraining processes to ensure long-term model accuracy and reliability. Ensure data quality through validation, testing, monitoring, and governance best practices. Partner with Data Engineering and IT to build and maintain scalable analytics infrastructure supporting production machine learning solutions. Business Impact Improve customer acquisition and retention through predictive analytics. Optimize pricing strategies through price elasticity modeling and customer response analytics. Optimize marketing campaigns and sales channel performance using data-driven insights. Increase operational efficiency through scalable automation and reusable analytical assets. Deliver accurate, validated insights that influence strategic business decisions. Build sustainable machine learning solutions that create long-term competitive advantage.

Qualifications: Required Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Marketing Analytics, or a related quantitative field.7+ years of experience in data science, machine learning, or advanced analytics. Strong programming skills in Python and SQL.Experience with Big Query, Big Query ML, and cloud-based analytical environments. Hands-on experience with machine learning libraries such as scikit-learn, XGBoost, LightGBM, and pandas. Strong understanding of predictive modeling, statistical analysis, experimentation, feature engineering, model validation, and machine learning best practices. Experience building machine learning models and automated analytical pipelines. Excellent communication skills with the ability to translate complex analytical findings into business recommendations. Preferred Masters degree in Data Science, Statistics, Computer Science, Analytics, or a related field. Telecommunications industry experience. Experience with Power BI or similar visualization platforms. Experience with speech analytics platforms (NICE, Verint, Call Miner), natural language processing (NLP), and Generative AI/LLM applications.