Job Summary:

The Senior Data Science Developer will lead the design and implementation of advanced analytics, predictive models, and AI-driven solutions to solve critical business challenges. This role involves applying statistical and machine learning techniques to enterprise data, supporting data maturity initiatives, validating models, and collaborating with cross-functional teams to operationalize analytics capabilities.

Responsibilities:

- Design and develop advanced analytics and machine learning models for key business use cases.
- Perform exploratory data analysis to uncover patterns and insights for decision-making.
- Translate business problems into analytical hypotheses, methodologies, and success metrics.
- Assess data quality, availability, and readiness for AI and analytics projects.
- Support enterprise data maturity and analytics capability assessments.
- Validate model performance and communicate assumptions, limitations, and results.
- Partner with stakeholders to identify high-value AI opportunities and assess feasibility and business impact.
- Develop prototypes and proofs of concept to test analytical approaches.
- Collaborate with Data Engineers, Architects, and Product Managers to operationalize models.
- Define and monitor analytical KPIs to measure solution effectiveness.
- Communicate complex findings clearly to technical and executive audiences.
- Apply Responsible AI, privacy, data governance, and model risk principles throughout the analytics lifecycle.

Required Skills:
- Expertise in statistics, probability, predictive modeling, and machine learning techniques including classification, regression, clustering, feature engineering, and model validation.
- Proficiency in Python, SQL, and machine learning frameworks.
- Experience building, tuning, and validating models using real-world enterprise datasets.
- Knowledge of data quality, experimentation, and analytical methodologies.




- Hands-on experience with Azure Machine Learning, Microsoft Foundry/Azure AI Foundry, and end-to-end ML pipelines.
- Strong communication, problem-solving, and stakeholder management skills.
- Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field, or equivalent experience.

Desired Skills:
- Experience with cloud-based data and analytics environments.
- Understanding of Generative AI and emerging AI techniques.
- Familiarity with Power BI, VSCode, Git, Jira, Databricks, and Azure OpenAI services.
- Strong business acumen with ability to link analytics to measurable business outcomes.

Rated Criteria:
- Advanced Machine Learning & Predictive Modeling Expertise - 30 Points
- Python and SQL Proficiency - 20 Points
- Model Validation and Experimentation Skills - 15 Points
- Cloud Analytics & Azure ML Experience - 15 Points
- Business Acumen and Stakeholder Communication - 10 Points
- Data Quality Assessment and Data Maturity Support - 10 Points

Total: 100 Points Deliverables:
- Advanced predictive models and machine learning solutions for priority business challenges.
- Exploratory data analysis reports identifying key trends and opportunities.
- Validated models with documented assumptions, limitations, and performance metrics.
- Prototypes and proofs of concept demonstrating analytical approaches.
- Operationalized ML pipelines integrated with enterprise data platforms.
- Analytical KPIs and outcome measurement reports.
- Explicit communication materials for technical and executive stakeholders.

Must Haves:
- Deep expertise in statistics, predictive modeling, and machine learning techniques.
- Advanced hands-on proficiency with Python, SQL, and ML frameworks.
- Experience with Azure Machine Learning and Microsoft Foundry/Azure AI Foundry platforms.
- Proven track record of building, tuning, and validating models using enterprise datasets.
- Strong communication and stakeholder management capabilities.

Public Sector Experience:

Preferred

📌 Senior Data Scientist (Ontario)
🏢 vTech Solution
📍 Ontario