Sr. Data Scientist to support advanced analytics and GenAI initiatives using Python, SQL, and machine learning - 1836

S.I. Systems Ltd.; Toronto; Hybrid; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Hybrid work model

12-month contract

Job summary

S.I. Systems Ltd. in Downtown Toronto is seeking a Sr.

Data Scientist to support advanced analytics and GenAI initiatives. The role focuses on execution-oriented data science and ML projects, including structured and unstructured data analysis, model development, and GenAI applications. You will collaborate with cross-functional teams on multiple projects over a 12-month maternity leave coverage, mentoring junior data scientists and data engineers, and leveraging Python, SQL, PySpark, and

Qualifications

• 5+ years of experience developing and deploying data science techniques.
• Proficiency in Python for data science and GenAI development.
• Complex SQL and PySpark queries across multiple sources.
• Experience with ML including supervised/unsupervised models.
• Experience with structured vs unstructured data and data transformation.
• Familiarity with APIs, microservices, and cloud-native development.
• Hands-on GenAI frameworks and LLM APIs with chatbot/agent experience.
• Understanding of RAG, prompt engineering, vector databases, and embeddings.
• Strong communication to explain technical concepts to stakeholders.
• Ability to manage multiple projects and mentor others.
• Bachelor’s degree or equivalent experience in a relevant field.

Responsibilities

• Translate business goals into analytical problems and select suitable ML/GenAI approaches.
• Collaborate in cross-functional teams to develop ML/data science products and GenAI apps.
• Apply descriptive, predictive, and ML methods from design to deployment.
• Focus on feature engineering, model training/evaluation, and prompt engineering for LLMs.

Skills

Python

GenAI

SQL

PySpark

Machine learning

Data transformation

APIs

Microservices

Cloud-native

LLM APIs

Agent development

Vector databases

Embedding models

Chatbots

Communication

Mentoring

Problem solving

Education

Bachelor’s degree in CS/Statistics/Math or related field

Tools

AWS SageMaker

AWS Glue

LangChain

Job description

Sr. Data Scientist to support advanced analytics and GenAI initiatives using Python, SQL, and machine learning - 1836

Location: Downtown Toronto - Hybrid (3 days on-site with Thursday being the team collaboration day)

Must be eligible for Reliability Clearance (Must have lived in Canada for 5 consecutive years)

Join a data analytics team supporting advanced analytics and GenAI initiatives within a large insurance environment. This role focuses on execution-oriented support for data science and machine learning projects, including structured and unstructured data analysis, model development, and GenAI applications. The position supports senior team members on focused project delivery within cross-functional teams. This is a 12-month contract supporting coverage for a maternity leave.

Must Haves

• 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
• 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
• Bachelor’s degree in computer science, Statistics, Mathematics, or related field, or equivalent experience

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.

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 community

Duration: 12 months to start

Disclaimer:

AI may be used in evaluating candidates.

This posting is for an existing vacancy.