Opens LinkedIn
- Employment type
- Contract
- Experience level
- Senior · 5+ years
- Minimum education
- Bachelor’s degree
- Posting language
- English
- Working hours
- 40 hours per week
- Office presence
- 3 days per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available
Job summary
Translate business objectives into analytical and machine learning solutions, and develop, deploy, and monitor end-to-end models using structured and unstructured data. Design Generative AI applications such as assistants, chatbots, RAG solutions, and autonomous agents, while collaborating with stakeholders, documenting solutions, presenting recommendations, and mentoring junior team members.
Job details
Job Title: Data Scientist Location: Toronto, ON (hybrid/ three days onsite) Duration: Long term Contract(12 months) Rate: CAD60-CAD65/hr Role Summary We are seeking an experienced Senior Data Scientist to support the development and adoption of advanced analytics, machine learning, and Generative AI solutions. The successful candidate will leverage expertise in data science, AI/ML, and cloud technologies to design, develop, and deploy innovative solutions that solve complex business problems and generate measurable value. Key Responsibilities Data Science & Machine Learning Translate business objectives into analytical and machine learning solutions. Apply statistical, predictive, and machine learning techniques to solve business challenges. Develop and deploy end-to-end ML models, including feature engineering, model training, validation, and monitoring. Work with both structured and unstructured data to generate actionable insights. Generative AI & AI Agents Design, develop, and implement GenAI solutions, including AI assistants, chatbots, and autonomous agents. Build and optimize Retrieval-Augmented Generation (RAG) solutions and intelligent search capabilities. Develop applications using modern GenAI frameworks and large language model (LLM) technologies. Implement prompt engineering, vector search, embeddings, and agent orchestration techniques. Technical Leadership & Collaboration Collaborate with cross-functional teams to deliver scalable AI and analytics solutions. Create technical documentation, solution designs, and implementation plans. Present findings and recommendations to business and technical stakeholders. Mentor junior team members and promote best practices in data science and AI development. Required Qualifications Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related field. 5+ years of experience in Data Science, Machine Learning, or Advanced Analytics. Strong proficiency in Python, SQL, and data manipulation techniques. Experience with machine learning models, statistical analysis, and predictive analytics. Hands-on experience with Generative AI, LLMs, RAG architectures, prompt engineering, and AI agent development. Experience working with APIs, microservices, and cloud-native architectures. Knowledge of vector databases, embedding models, and conversational AI solutions. Strong communication, problem-solving, and stakeholder management skills. Ability to manage multiple priorities in a fast-paced environment. Nice to Have Experience with cloud platforms such as AWS, including AI/ML services. Experience with data engineering, ETL pipelines, data warehousing, and big data technologies. Familiarity with workflow orchestration and automation tools. Experience mentoring junior Data Scientists and Data Engineers.
What you’ll do
Translate business objectives into analytical and machine learning solutions, and develop, deploy, and monitor end-to-end models using structured and unstructured data. Design Generative AI applications such as assistants, chatbots, RAG solutions, and autonomous agents, while collaborating with stakeholders, documenting solutions, presenting recommendations, and mentoring junior team members.
Requirements
Requires a bachelor's degree in a relevant field and at least five years of experience in data science, machine learning, or advanced analytics, with strong Python and SQL skills. Candidates should have hands-on experience with Generative AI, LLMs, RAG, prompt engineering, AI agents, APIs, microservices, and cloud-native architectures, along with strong communication and problem-solving skills.
Listed skills
- Python · Preferred
- SQL · Preferred
- Machine learning · Preferred
- prompt engineering · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- SQL
- Data Science
- Machine Learning
- Statistical Analysis
- Predictive Analytics
- Generative AI
- Large Language Models
- Retrieval-Augmented Generation
- Prompt Engineering
- AI Agent Development
- Vector Search
- Embedding Models
- APIs
- Microservices
- Cloud-Native Architectures
Job areas
- Data & Analytics
- Technology
- Software
- Science & Research
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