GTM Analytics Lead owning revenue data models, metrics, and Sales BI. Powering decisions for ButterflyMX’s smartphone - based building access platform.
About the role
- Data Scientist working with R&D and product development to create AI-driven metrics and models. Contributing to smart concrete testing technologies at Giatec Scientific in Ottawa, Ontario.
Responsibilities
- Develop and implement advanced machine learning models and algorithms for prediction, analysis, and optimization of concrete performance
- Optimize models for improved accuracy, robustness, and performance
- Build and maintain agentic AI systems capable of multi-step reasoning, tool usage, and workflow orchestration
- Utilize strong knowledge of machine learning frameworks such as Keras, TensorFlow, or similar tools to develop and fine-tune models
- Stay up to date with the latest advancements in data science, machine learning, large language models, and agentic AI
- Apply expertise in Python and SQL to manipulate, analyze, and transform large datasets
- Develop retrieval-augmented generation (RAG) pipelines by integrating structured and unstructured data sources with LLMs
- Develop, and deploy LLM-based solutions to support intelligent reasoning, automation, and decision-making within products and internal tools
- Solve complex problems using data-driven and AI-powered approaches
Requirements
- Master’s or PhD in Data Science, Computer Science, Statistics, Mathematics, or a related field
- Proficiency in programming languages such as Python
- Proven experience leveraging machine learning frameworks such as Keras, TensorFlow, or similar tools
- Strong understanding of prompt engineering, LLM evaluation techniques, and reliability considerations
- Familiarity with retrieval-augmented generation (RAG) architectures and vector search technologies
- Enthusiasm for learning new technologies and sharing knowledge with others
- Demonstrated experience analyzing, modeling, training, and deploying machine learning and AI solutions into production
- Proficiency with data science libraries such as pandas, NumPy, and Matplotlib
- Experience building agent-based or agentic AI systems using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent
- Hands-on experience working with Large Language Models (LLMs) (e.g., OpenAI, Azure OpenAI, Hugging Face, or similar platforms)
- Hands-on experience with databases such as PostgreSQL and MongoDB, including efficient data querying and manipulation
- Strong experience applying supervised and unsupervised machine learning techniques to build predictive and prescriptive solutions
Benefits
- Hybrid work week
- Competitive company-paid benefits plan
- Generous professional development budget
- Volunteer and Life Days that make work/life balance easier to achieve
- Your birthday off (because we want you to celebrate)
- RRSP matching program through RBC
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