Senior WMS Implementation Engineer

Job summary

Develop and implement data science and machine learning solutions, including generative AI applications, agents, chatbots, and intelligent retrieval systems. Collaborate with stakeholders and cross-functional teams to plan technical work, create design artifacts, communicate findings, and advance analytics initiatives.

Job details

Job Title: Data Scientist Location: Toronto, ON (Hybrid 3 days onsite) Duration: 12 Months contract with possibility of extension Pay Rate: $95-100/hour CAD on Inc. Job Description: Reporting to the Director, Data Science, as a Senior Data Scientist a successful candidate will focus on supporting Canadian business units in accelerating the growth and application of advanced analytics in driving value. The senior data scientist will leverage practical experience in applying varied data science techniques & offering advice/inputs to help with the design, development and implementation of analytics use cases. Key Responsibilities: Data Science and Machine Learning 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 GenAI & Agentic AI Development 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 Technical Leadership & Collaboration 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 communications. Required Qualifications: Bachelor’s degree in computer science, Statistics, Mathematics, or related field, or equivalent experience 0-3+ 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 Strong 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 engineers Strong problem-solving abilities and analytical skills with keen attention to detail Nice to Have: Experience with AWS services including SageMaker, Lambda, Bedrock, and other AI/ML services Experience with data warehousing, pipelines, and big data technologies such as AWS Glue for ETL, Glue Catalog, Glue Data Quality, and AWS Step Functions.

What you’ll do

Develop and implement data science and machine learning solutions, including generative AI applications, agents, chatbots, and intelligent retrieval systems. Collaborate with stakeholders and cross-functional teams to plan technical work, create design artifacts, communicate findings, and advance analytics initiatives.

Requirements

Requires a bachelor's degree in computer science, statistics, mathematics, or a related field, or equivalent experience, along with experience developing data science techniques. Candidates should be proficient in Python, SQL, PySpark, machine learning, GenAI and LLM frameworks, RAG, APIs, and cloud-native development, with strong communication and problem-solving skills.

Listed skills

• SQL · Preferred
• Machine learning · Preferred
• prompt engineering · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• SQL
• PySpark
• Machine Learning
• Data Science
• Generative AI
• AI Agent Development
• Retrieval-Augmented Generation
• Prompt Engineering
• Large Language Models
• Vector Databases
• Feature Engineering
• Model Evaluation
• API Development
• Cloud-Native Development
• Stakeholder Communication

Job areas

• Data & Analytics
• Technology
• Software
• Science & Research

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