Senior Data Scientist to provide hands-on support and direction on strategic data initiatives i[...]

S I Systems; Ottawa, Vancouver, Edmonton, Calgary, Halifax; Remote; CAD 90,000 - 120,000; Full time

Job summary

A leading company is seeking a Senior Data Scientist to drive strategic data initiatives, focusing on AI, ML, and data product design for a public sector client. This fully remote role requires extensive experience in data analysis and modeling, along with strong client communication skills. The candidate will mentor team members, enhance data quality, and align analytics with departmental strategies. This position offers the opportunity to work with large datasets and make impactful contributions to data-driven decision-making.

Qualifications

• 6+ years as a Data Analytics Specialist or Data Scientist.
• Experience with AI & ML, data modeling, and statistical analysis.

Responsibilities

• Provide expertise on strategic data initiatives and develop data models.
• Coordinate with clients to understand analytics needs and enhance data quality.
• Create presentations for senior management and facilitate strategic discussions.

Skills

Data Analysis

Statistical Analysis

AI

Machine Learning

Data Product Delivery

Client Communication

Tools

R

Python

SQL

Hadoop

Spark

Azure

Snowflake

Job description

Senior Data Scientist to provide hands-on support and direction on strategic data initiatives including AI, ML and data product design for a public sector client (593)

Job Type: Contract

Positions to fill: 1

Job End Date: Jun 29, 2026

Pay Rate: Hourly: Negotiable

Job ID: 145348

Our client is seeking a Senior Data Scientist to provide hands-on support and direction on strategic data initiatives including AI, ML and data product design for a public sector client.

This is a fully remote role though occasional travel to Edmonton may be required at the consultant's own expense.

Must Haves:

• 6+ years as a Data Analytics Specialist or Data Scientist with experience in data analysis, data modelling, statistical analysis, AI & ML, and data product delivery.
• Proficiency in statistical and programming languages such as R, Python, SQL.
• Experience in building analytical and quantitative models.
• Experience with data science, data engineering, and AI projects.
• Ability to prepare data for prescriptive and predictive modeling.
• Skill in understanding complex business questions and framing analytical solutions.
• Knowledge of various data analytics and data science methods, including complex statistical modeling.
• Understanding of statistical and data mining techniques to address business issues.

Additional Experience:

• 5+ years in data sharing, data linkage, de-identification, metadata, data quality, ethics, synthetic data, and data literacy.
• Experience integrating raw data from diverse sources.
• Client communication skills, especially explaining complex data principles.
• Experience creating visualizations, dashboards, and analytical models.
• Understanding of analytical project requirements.
• 3+ years designing and maintaining data pipelines and workflows.
• Experience with big data technologies (e.g., Hadoop, Spark) or cloud platforms (Azure, Snowflake).
• Experience working with large government datasets.

About the Role:

The candidate will be a versatile Data Analytics Specialist / Data Scientist, involved in data analysis, modeling, AI & ML, and data product delivery. The role includes data engineering, technical analysis, and business analysis aspects.

Responsibilities include providing expertise on strategic data initiatives, coordinating with clients to understand analytics needs, and developing data models and products. The role requires anticipating complex data requirements, aligning with departmental strategies, and evolving services based on emerging needs.

Key activities involve designing analytic projects, developing data models, improving analytics capacity, and creating analytic service offerings. The candidate will analyze raw data, evaluate business needs, enhance data quality, and collaborate with engineers and analysts. Mentoring team members and engaging with stakeholders to promote data as a strategic asset are crucial.

The role also involves creating presentations for senior management, facilitating strategic discussions, developing metrics, and applying techniques like probability models, machine learning, and data visualization to extract insights from data.