Senior Data Specialist

BITS Recruiting; Toronto; On-site; CAD 103,000 - 110,000; Full time

Job summary

BITS Recruiting is seeking a Senior Data Analytics Specialist/Scientist for a contracted engagement in Toronto, Canada. You will lead analytics initiatives, build models, and deliver data-driven insights to support evidence-based decisions across business units.

The role involves statistical modelling, ML, data engineering, BI, and emerging AI/LLM tech, working with data architects and ETL teams to translate requirements into scalable analytics solutions.

Qualifications

• 3–5+ years of relevant experience in data analytics, data science, or a related discipline.
• Hands-on experience with Microsoft Azure data and analytics tools.
• Experience with Azure Databricks.
• Hands-on experience with MLflow for machine learning lifecycle management.
• Strong programming experience with Python.
• Experience with Python data science libraries such as pandas, scikit-learn, PyTorch, or equivalent.
• Exposure to LLM/Generative AI frameworks, such as LangChain, DSPy, Equivalent LLM/AI frameworks.
• Experience working with large, complex datasets including structured and unstructured data.
• Strong knowledge of machine learning, statistical analysis, data mining, and analytical modelling.
• Strong SQL/querying skills and experience developing complex queries.
• Experience translating business requirements into data, analytics, and BI solutions.
• Strong communication skills with the ability to explain technical and analytical concepts to both technical and non-technical stakeholders.

Responsibilities

• Lead the development and delivery of business and ministry-specific analytics to support evidence-based decision-making.
• Assess existing data analytics, reporting, and BI capabilities and identify opportunities for improvement.
• Gather and translate business requirements into analytical and technical solutions.
• Own analytics initiatives from requirements gathering through development, testing, deployment, and delivery.
• Develop statistical models and machine learning algorithms to identify trends, model business scenarios, and generate actionable insights.
• Design processes to capture, structure, transform, and prepare data for analytics and machine learning.
• Build reliable and accurate data models using structured and unstructured data sources.
• Analyze high-volume datasets and identify patterns, trends, anomalies, and opportunities.
• Collaborate with Data Architects, ETL Developers, business SMEs, and stakeholders to design effective data and BI solutions.
• Support the development and implementation of AI/ML and LLM-based analytical solutions where appropriate.
• Participate in solution design, documentation, development, testing, and end-user training.
• Develop dashboards, visualizations, reports, and analytical outputs that clearly communicate findings.
• Translate complex quantitative analysis into clear recommendations and actionable business insights.
• Provide analytical guidance and recommendations to stakeholders and leadership.
• Identify opportunities to improve business processes through data, analytics, automation, and AI.
• Ensure analytical outputs are accurate, reliable, understandable, and appropriately validated.

Skills

Python

SQL

Azure

Azure Databricks

MLflow

Pandas

scikit-learn

PyTorch

LangChain

DSPy

LLM/Generative AI

Data modelling

Data visualisation

Tools

Azure Databricks

MLflow

SQL

Job description

Senior Data Analytics Specialist / Scientist

Contract: August 17, 2026 – December 31, 2026

Potential Extension: 1 extension term

Incorp Rate: $75-$79.78/hr

Position Overview

Our client is seeking a Senior Data Analytics Specialist / Scientist to lead the development and delivery of advanced analytics solutions that support evidence-based decision-making.

The successful candidate will work closely with business stakeholders, data architects, ETL developers, and technical teams to understand complex business problems, define analytical requirements, develop data-driven solutions, and translate complex findings into actionable insights.

The role will involve data analytics, statistical modelling, machine learning, data engineering, business intelligence, and emerging AI/LLM technologies.

Must-Have Qualifications

• 3–5+ years of relevant experience in data analytics, data science, or a related discipline.


• Strong hands-on experience with Microsoft Azure data and analytics tools.


• Experience with Azure Databricks.


• Hands-on experience with MLflow for machine learning lifecycle management.


• Strong programming experience with Python.


• Experience with Python data science libraries such as pandas, scikit-learn, PyTorch, or equivalent.


• Exposure to LLM/Generative AI frameworks, such as:


• LangChain


• DSPy


• Equivalent LLM/AI frameworks


• Experience working with large, complex datasets, including structured and unstructured data.


• Strong knowledge of machine learning, statistical analysis, data mining, and analytical modelling.


• Strong SQL/querying skills and experience developing complex queries.


• Experience translating business requirements into data, analytics, and BI solutions.


• Strong communication skills with the ability to explain technical and analytical concepts to both technical and non-technical stakeholders.

Key Responsibilities

• Lead the development and delivery of business and ministry-specific analytics to support evidence-based decision-making.


• Assess existing data analytics, reporting, and BI capabilities and identify opportunities for improvement.


• Gather and translate business requirements into analytical and technical solutions.


• Own analytics initiatives from requirements gathering through development, testing, deployment, and delivery.


• Develop statistical models and machine learning algorithms to identify trends, model business scenarios, and generate actionable insights.


• Design processes to capture, structure, transform, and prepare data for analytics and machine learning.


• Build reliable and accurate data models using structured and unstructured data sources.


• Analyze high-volume datasets and identify patterns, trends, anomalies, and opportunities.


• Collaborate with Data Architects, ETL Developers, business SMEs, and stakeholders to design effective data and BI solutions.


• Support the development and implementation of AI/ML and LLM-based analytical solutions where appropriate.


• Participate in solution design, documentation, development, testing, and end-user training.


• Develop dashboards, visualizations, reports, and analytical outputs that clearly communicate findings.


• Translate complex quantitative analysis into clear recommendations and actionable business insights.


• Provide analytical guidance and recommendations to stakeholders and leadership.


• Identify opportunities to improve business processes through data, analytics, automation, and AI.


• Ensure analytical outputs are accurate, reliable, understandable, and appropriately validated.

Technical & General Skills

• Strong analytical, problem-solving, investigative, and decision-making skills.


• Excellent written and verbal communication skills.


• Strong consulting and stakeholder management capabilities.


• Ability to facilitate requirements sessions and translate business needs into technical solutions.


• Experience working with both technical and non-technical audiences.


• Knowledge of:


• Statistical analysis and modelling


• Machine learning and algorithms


• Natural language processing


• Generative AI / LLM technologies


• Data management


• Experience developing ETL/data transformation processes for large relational or multidimensional data stores.


• Strong understanding of data quality, validation, and governance.


• Experience designing user-friendly analytical interfaces and dashboards.


• Proficiency with SQL and complex query development.


• Experience with one or more programming/scripting languages, with Python strongly preferred.


• Strong understanding of mathematics and statistics.


• Ability to work independently while collaborating effectively within cross-functional teams.

Nice-to-Have Skills

Experience with analytical and statistical tools such as:

• R


• MATLAB


• SPSS


• SAS


• Microsoft Excel


• Microsoft Access


• VBA

Experience with additional cloud, BI, machine learning, or AI technologies is an asset.