Translate business goals into analytical problems; Identify optimal algorithms, statistical techniques and/or GenAI architecture suitable for the business problem at hand Work in cross-functional teams to develop ML/data science products, including GenAI applications Apply best-in-breed data science techniques including descriptive, predictive, and machine learning methods from design to implementation Focus on feature engineering, model training, model evaluation, and prompt engineering for LLMs Design, develop, and deploy GenAI solutions including AI agents, chatbots, and autonomous systems that solve complex business problems Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques, and agentic frameworks (LangChain, LangGraph, CrewAI etc.) Implement AI bots/agents with advanced reasoning capabilities and tool use patterns Work with vector databases and embedding models to build intelligent information retrieval systems Break down broader data science development milestones into actionable goals, activities, and work plans Create and maintain technical design artifacts describing application functionality, data models, interfaces, and integrations Engage and negotiate with stakeholders, make business recommendations with effective presentations of findings at multiple levels of stakeholders Champion continuous improvement and foster innovation within the analytics community. Requirements Bachelor’s degree in computer science, Statistics, Mathematics, or related field, or equivalent experience 5+ years experience in developing and implementing data science techniques Proficient in Python for data science and GenAI application development Experience with writing complex SQL and PySpark queries to extract and integrate data from multiple database sources Proficiency in machine learning including supervised and unsupervised models Demonstrated experience in data transformation, data manipulation, and working with structured vs.



unstructured data Robust understanding of APIs, microservices architecture, and cloud-native development Hands-on expertise with GenAI frameworks and LLM APIs with experience developing AI bots/agents with reasoning and tool-use capabilities Strong understanding of RAG techniques, prompt engineering, and fine-tuning methodologies and familiarity with vector databases and embedding models Experience with chatbot development concepts and conversational AI design Exceptional communication skills to articulate complex technical concepts to both technical and non-technical stakeholders Effective and concise oral and written storytelling and insights communication skills Ability to work on multiple projects in parallel while managing constantly changing deadlines and priorities Proven ability to mentor and guide junior data scientists and data engineersStrong problem‑solving abilities and analytical skills with keen attention to detail. Core Competencies Proficient in developing and implementing data science techniques, with a strong focus on GenAI application development, machine learning, and advanced data manipulation. Demonstrates exceptional communication skills to effectively present complex technical concepts to diverse stakeholders. Highest-signal resume keywords Python Proficiency Machine Learning Expertise GenAI Frameworks Experience SQL and PySpark Skills Chatbot Development Knowledge ATS Optimization Keywords Hard Skills Data Science Techniques Feature Engineering Model Training Model Evaluation Data Transformation Data Manipulation APIs Understanding Microservices Architecture RAG Techniques Prompt Engineering Soft Skills Exceptional Communication Skills Effective Storytelling Problem‑Solving Abilities Analytical Skills Mentoring and Guiding Industry Keywords Cross-Functional Teams Continuous Improvement Data Science Development Conversational AI Design Stakeholder Engagement Tools & Technologies GenAI Applications LLM APIs Vector Databases Embedding Models AI Agents Chatbots #J-18808-Ljbffr

📌 Senior Data Scientist (Toronto)
🏢 Jobtailor
📍 Toronto