Lead Data Scientist

Location: Esquimalt

Ready to be a Titan?

As the Lead Data Scientist on our Operations data science team supporting the Finance organization, you will use machine learning, generative AI, and data-driven insights to drive financial planning, optimize spend, and inform strategic decision-making across Service Titan. Your work will directly impact some of Service Titan's most critical financial decisions and help shape how the company forecasts, plans, and allocates resources s is a rare opportunity to blend machine learning and GenAI with strategic financial thinking at a fast-growing firm in a way that will be visible to top executives within Service Titan.

What you'll do:

Lead the design, development, and deployment of advanced machine learning, forecasting, optimization, and generative AI solutions that power financial planning, analysis, and decision-making

Partner closely with Finance leadership and other key business stakeholders to translate financial questions into rigorous data science problems

Build machine learning systems from the ground up and design scalable data science infrastructure that Finance teams can rely on Strategically determine the most appropriate modeling approach (traditional ML, forecasting, optimization, or Generative AI) for each problem, and design experiments to evaluate competing approaches

Deliver cutting-edge forecasting, anomaly detection, and optimization expertise, driving best practices across financial modeling at Service Titan Transform  model outputs into actionable, executive-ready business recommendations

Champion and execute long-term strategic projects that improve how Service Titan plans and operates financially

Collaborate closely with engineering and product teams to seamlessly deploy models into production, ensuring scalability and performance

Mentor data scientists on the team and elevate the technical bar across forecasting, optimization, and GenAI work Invent bold and creative solutions to current and future business problems

What you’ll bring:

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.

Education:

MS/Ph.D in Data Science, Statistics, Applied Mathematics, Engineering, or similar quantitative discipline.

Core Technical Stack:
Strong proficiency in SQL and Python, with deep expertise in the data science ecosystem (e.g., PyTorch, Transformers, scikit-learn, XGBoost/Light

GBM, scipy, stats models).Forecasting & Optimization:
Deep experience building and deploying forecasting models and resource-constrained optimization models in production environments.

Generative AI & Agents:

Demonstrated experience applying Generative AI to real business problems, including practical experience developing and testing GenAI solutions

Experience building Agentic Workflows and implementing RAG architectures

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.

Cloud

Infrastructure: Hands-on experience with cloud platforms, with a strong preference for Microsoft Azure (e.g., Azure AI Studio, Foundry).Business Acumen:
Ability to combine model results with clear business understanding to create actionable recommendations, particularly in financial or operational contexts.

Soft Skills:

Excellent communication skills, including translating complex technical concepts into actionable insights for finance and executive stakeholders. Proactive and collaborative mindset.

Passion for discovery, problem solving, and practical business outcomes in partnership with finance and engineering leadership.

Preferred experience:

Experience supporting Finance, FP&A, or related functions with data science solutions

Experience building and deploying MCPsBe Human With Us:

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