Data Analytical Specialist Scientist 9753-1712

HM Note: This hybrid contract role is five (5) days in office. Candidate resumes must include first and last name, email and telephone contact information.

Description

Responsibilities:

• Lead the development and delivery of functional and ministry-specific analytics to support evidence-based decision-making and produce actionable insights.
• Work closely with client's groups to assess current data analytics and reporting capabilities, gather future-state requirements and identify further opportunities for improvement.
• Facilitate decision-making and manage client expectations.
• Own the execution of analytics initiatives including end-to-end reporting and data set delivery.
• Develop robust statistical models and machine learning algorithms to model business scenarios and extract valid inferences.
• Participate in documentation, development, testing, and end user training.
• Work with functional area experts, Data Architects and ETL Developers and stakeholders to understand complex business issues and develop appropriate Business Intelligence solutions.
• Design methods to capture, structure, transform, and process data to be used to generate models.
• Build data models that provide information which is accurate, easy to understand and unbiased.
• Communicate complex quantitative analysis in a clear and precise manner, providing useful visuals and summaries.
• Provide interpretation, advice, and expertise to client groups and other stakeholders, including direction on how to transform analytics into actionable information and proactive insights that support decision making.

General Skills:

• Excellent analytical, problem-solving and decision-making skills, verbal and written communication skills, interpersonal skills and team work skills.
• Outstanding consulting and relationship management skills, with proven ability to elicit requirements, develop/consult on options and solutions, and provide effective guidance
• Adept at communicating to both technical and non-technical audiences

• Experience with a range of analytical methods, techniques and tools such as, but not limited to:

• statistical analysis and modelling,

• data mining,
• machine learning and algorithms,
• natural language processing, and

• other related disciplines at the specified experience level

• Ability to manipulate and analyze complex, high-volume data from structured and unstructured sources

• Experience developing data extraction, transformation, and load functionality for large relational and multi-dimensional data stores
• Experience designing high quality interfaces to present information in a meaningful way to end users
• Broad understanding of data management, financial and business analysis, database architecture, and information visualization
• Proficiency in query languages and experience constructing complex query statements
• Experience in one or more programming or scripting languages Strong investigative and logic skills.
• Proficiency in mathematics and statistics Awareness of emerging Business Intelligence trends and directions
• Functional area experience as required
• Experience with analytical software such as R, PowerPivot, Matlab, SPSS, or SAS an asset
• Proficiency with desktop analysis software including Microsoft Excel, Access, VBA

Skills

Experience and Skill Set Requirements

Role Overview:

We are looking for a data scientist to support various initiatives related to the platform as well as the execution of use cases to support the needs of various businesses.

Key Responsibilities

• Run and Monitor Inferences

• Execute batch inference jobs on Databricks and other environments.

• Troubleshoot inference issues, log results, and escalate model anomalies.

• Pipeline & Evaluation Support

• Assist with running DSPy pipelines and loading custom models/configs.

• Support evaluation runs using internal metrics
• Track and summarize performance metrics for inference experiments.

• Data Handling & Experimentation

• Help prepare and clean legal text datasets for inference and evaluation.

• Annotate outputs to support error analysis and benchmarking.
• Maintain reproducible scripts/notebooks for inference runs.

• Qualifications

• Background in Computer Science, Data Science, or AI/ML (student or recent grad is good).

• Familiarity with Python and libraries like pandas, scikit-learn, or PyTorch.
• Exposure to LLM frameworks (DSPy, LangChain, Hugging Face, or equivalent).
• Comfortable working with Databricks / MLflow or other cloud ML environments.
• Detail-oriented with strong organizational skills for tracking experiments.

Must have:

• must have experience Azure data tools - azure, databricks, MLflow, python