Data Scientist (NO C2C / NO RELO!)

Here’s a cleaner, more engaging LinkedIn post version that will attract candidates and is easier to scan on LinkedIn: 🚀 Now Hiring: Data Scientist II – Model Validation & Monitoring We’re looking for a Data Scientist II to join our Model Validation & Monitoring team, where you’ll play a key role in ensuring the performance, reliability, and integrity of machine learning models delivered to our clients. This role is ideal for someone who enjoys challenging models, solving complex data problems, and working with large-scale datasets in a fast-paced environment. 🔎 What You’ll Do • Lead model monitoring activities including performance tracking, data/model drift detection, and data quality analysis • Perform rigorous model validation through performance testing, benchmarking, and documentation to ensure models meet business and regulatory standards • Conduct root cause analysis when model performance issues arise and recommend remediation strategies • Explore and analyze large datasets to identify data anomalies impacting algorithm performance • Develop production-level code in a dynamic environment • Apply machine learning techniques to solve complex business problems • Work with terabyte-scale datasets using Spark • Collaborate with Product and Engineering teams to identify trends and opportunities • Communicate insights and model results to non-technical stakeholders 📊 Basic Qualifications • Master’s degree in Mathematics, Statistics, Computer Science, Operations Research, or related field • 2+ years of experience in data science, engineering, or related fields • Experience building data science pipelines and workflows in Python, R, or similar • Strong SQL skills and experience with large datasets • Experience with Spark and machine learning libraries (e.g., scikit-learn, MLlib) • Ability to build production-ready, explainable code • Experience presenting complex analysis to non-technical audiences ⭐ Preferred Qualifications • PhD or advanced degree in a related field • Experience building or validating fraud detection models • Hands-on experience with PySpark • 2+ years of industry experience developing or validating ML models • Strong ability to work through ambiguity and deliver results in fast-moving environments • Experience identifying hidden patterns and data anomalies in large datasets 📩 If you’re passionate about machine learning, model validation, and data-driven problem solving, we’d love to connect. #DataScience #MachineLearning #Hiring #DataScientist #AI #ModelValidation #Python #Spark If you'd like, I can also create: