Lead Data Scientist

What You Get to Do: Technical & Architectural Leadership: • Define and own the ML and advanced analytics architecture supporting HR, benefits, and payroll products. • Design end-to-end, production-grade ML systems—from data ingestion and feature engineering to model serving, monitoring, and retraining. • Lead the selection and optimization of algorithms (tree-based models, deep learning, time- series forecasting, GenAI) with tradeoffs across accuracy, latency, scalability, and cost. • Establish best practices for model governance, explainability, bias detection, and compliance. Advanced Modeling & Forecasting: • Drive the development and validation of time-series and forecasting models (ARIMA/SARIMA, Prophet, state-space models, LSTM/transformers) for workforce planning, attrition, and financial forecasting. • Champion advanced experimentation, model evaluation frameworks, and statistical rigor across teams. • Leverage GenAI/LLMs where appropriate to enhance product intelligence and user experience. MLOps & Production Excellence: • Partner with DevOps and Platform teams to build robust MLOps pipelines using CI/CD, automated retraining, monitoring, and alerting. • Ensure reliable, secure, and scalable model deployment using containerized microservices. • Define SLAs, performance benchmarks, and operational metrics for ML services in production. Leadership & Collaboration: • Lead, mentor, and grow a team of senior and mid-level data scientists, fostering a culture of technical excellence and ownership. • Work closely with Product, Engineering, Security, and Compliance to translate business needs into scalable ML solutions. • Act as a trusted advisor to stakeholders, influencing product strategy and long-term data science roadmap. What You Bring: • 12+ years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production • Familiarity with the setup and use of various open source LLM foundation models. • Experience with creating and using vectorized databases for data storage and retrieval. • Familiarity with LLM architecture patterns such as RAG and FLARE. • Hands on experience with LLM Pretraining, LLM fine-tuning, RLHF, distillation, parameterefficient methods like LoRA, quantization • Bachelor's degree in Computer Science, Engineering, Mathematics or a related field is required Show more