Senior Data Scientist (Remote, Global)

About The Role Teramind is on a mission to reinvent how organizations understand work. With millions of behavioral signals flowing through our platform, we're unlocking a new era of intelligent workforce analytics - from predictive insights to behavior modeling and ML-powered decision-making. We're building a brand-new data science organization to make this vision real. And we're hiring a Senior Data Scientist who wants to build the models, pipelines, and intelligent systems that power the future of analytics at Teramind. If you thrive at the intersection of deep technical work, rapid experimentation, and real product impact - this is your role. What You’ll Do • Design and implement ML models for behavior prediction, anomaly detection, and risk scoring • Develop and fine-tune transformer-based models • Optimize models for production deployment—balancing accuracy, latency, and resource efficiency  • Build end-to-end pipelines from raw behavioral signals to production-ready features • Partner with product and engineering to translate business problems into data science solutions • Run rigorous experiments—A/B tests, causal inference, statistical validation—to measure real impact • Prototype rapidly, iterate based on customer feedback, and ship models that scale • Contribute to the technical foundations and best practices of a growing DS function What You Bring • Deep hands-on expertise in Python, SQL, and ML framework (TensorFlow, PyTorch, Scikit-learn, XGBoost) • 5+ years of experience shipping ML models to production with measurable product or business impact • Strong fundamentals in statistics, causal inference, and experimental design • Experience with transformer architectures • Familiarity with model optimization for production constraints • Comfort working in ambiguity—scoping problems, finding data, and driving to solutions independently • Experience with large-scale data processing (Spark, BigQuery, or similar) is a plus • Master's degree in a quantitative discipline such as Statistics, Engineering, Computer Science, or equivalent practical experience