Lead Data Scientist

About the role

Join ServiceTitan as a Lead Data Scientist on our Operations data science team supporting the Finance organization. You will leverage machine learning, generative AI, and data-driven insights to drive financial planning, optimize spending, and inform strategic decision-making. Your work will directly impact critical financial decisions and shape how the company forecasts, plans, and allocates resources. You will lead the design, development, and deployment of advanced machine learning solutions, collaborate closely with Finance leadership, and mentor data scientists on the team. Key missions: Concevoir, développer et déployer des solutions avancées d'apprentissage automatique, de prévision, d'optimisation et d'IA générative qui alimentent la planification financière, l'analyse et la prise de décision.. Collaborer étroitement avec la direction financière et d'autres parties prenantes clés pour traduire les questions financières en problèmes de science des données rigoureux.. Construire des systèmes d'apprentissage automatique depuis le début et concevoir une infrastructure de science des données évolutive sur laquelle les équipes financières peuvent compter. Profile: - Being human isn’t about checking every box on a list. It’s about the experiences we have, people we meet, and the perspectives we share. So, if you have the skills but are hesitant to apply because of your background, apply anyway - Generative AI & Agents: - Soft Skills: Excellent communication skills, including translating complex technical concepts into actionable insights for finance and executive stakeholders. Proactive and collaborative mindset - Forecasting & Optimization: Deep experience building and deploying forecasting models and resource-constrained optimization models in production environments - Passion for discovery, problem solving, and practical business outcomes in partnership with finance and engineering leadership - Cloud Infrastructure: Hands-on experience with cloud platforms, with a strong preference for Microsoft Azure (e.g., Azure AI Studio, Foundry) - Education: MS/Ph.D in Data Science, Statistics, Applied Mathematics, Engineering, or similar quantitative discipline - Experience: 8+ years as a data scientist developing predictive business models, with at least 5 years of experience in time series forecasting, anomaly detection, and/or optimization. Proven track record of delivering impactful, production-grade solutions - Demonstrated experience applying Generative AI to real business problems, including practical experience developing and testing GenAI solutions - Business Acumen: Ability to combine model results with clear business understanding to create actionable recommendations, particularly in financial or operational contexts - Statistical Rigor: Strong foundation in statistics, including hypothesis testing, experimental design, and causal inference to ensure the reliability of analytical insights and model impact evaluation - Core Technical Stack: Strong proficiency in SQL and Python, with deep expertise in the data science ecosystem (e.g., PyTorch, Transformers, scikit-learn, XGBoost/LightGBM, scipy, statsmodels) - Experience building Agentic Workflows and implementing RAG architectures - Experience supporting Finance, FP&A, or related functions with data science solutions - Experience building and deploying MCPs