RQ07955 - Sr. Data Analytical Specialist / Scientist

Rubicon Path; Toronto; On-site; CAD 85,000 - 110,000; Full time

Job summary

A data-driven consulting firm in Toronto is seeking a Senior Data Analytical Specialist. In this role, you will lead analytics initiatives and support evidence-based decision-making. The ideal candidate will have deep expertise in SQL, data analysis, and modelling, along with the ability to communicate complex analyses clearly. Experience with data visualization tools such as PowerBI is preferred.

Qualifications

• Knowledge of information management and data management.
• Ability to analyze data quality issues.
• Experience with data modeling methods.

Responsibilities

• Lead the development of functional analytics.
• Assess data analytics and reporting capabilities.
• Manage client expectations and facilitate decision-making.
• Develop statistical models and machine learning algorithms.
• Communicate complex analyses clearly.

Skills

Structured Query Language (SQL)

Data mining

Statistical analysis

Machine learning

Deep learning

Natural language processing

Python

R

Tools

R Shiny

PowerBI

Job description

About the job

RQ07955 - Sr. Data Analytical Specialist / Scientist

Must Haves :

• Demonstrates efficiency in Structured Query Language (SQL) to access databases to conduct research and use applications to retrieve and manipulate data from databases located on different platforms.
• Demonstrate knowledge of data skills, methods, techniques, and tools, including data mining, statistical analysis, statistical models and algorithms on machine learning, deep learning, natural language processing, artificial intelligence and other related disciplines
• Ability to analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)
• Use creative thinking and propose innovative ways as it relates to data mining, behavioural economics, statistics and statistical models, algorithms, data integration, information management, predictive analytics and analytics modeling, and data-related information technology

Nice to Have :

• Experience with coding skills in various data languages (e.g. R, Python) and proficiency with various, modeling, analytics and data visualization software tools (R Shiny, PowerBI, etc.)

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 clients 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

Knowledge Transfer

Transfer From Data Analytical Specialist / Scientist - Senior to Project Manager

Skills Experience and Skill Set Requirements

Technical Knowledge / Skills - 50%

• Demonstrate knowledge of information management, data management, financial and business analysis, database architecture, and data related concepts such as data preparation, data integration, data anonymization, data extract / transform / load (ETL), data warehousing, data lineage, metadata management, master data management, and data governance
• Demonstrate knowledge of data skills, methods, techniques, and tools, including data mining, statistical analysis, statistical models and algorithms on machine learning, deep learning, natural language processing, artificial intelligence and other related disciplines
• Demonstrates efficiency in Structured Query Language (SQL) to access databases to conduct research and use applications to retrieve and manipulate data from databases located on different platforms.
• Experience with coding skills in various data languages (e.g. R, Python) and proficiency with various, modeling, analytics and data visualization software tools (R Shiny, PowerBI, etc.)
• Experience in the use of data modelling methods and tools (e.g. PowerDesigner) including a working knowledge of metadata structures, repository functions, and data dictionaries
• Understand legislative regulations, policies and guidelines, ministry programs / services and policy development processes, data standards (e.g. GO-ITS) and privacy legislation (e.g. FIPPA) related to access and release of personal information and data

Research, Analytical and Problem-Solving Skills - 40%

• Ability to analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)
• Manipulate and analyze complex, high-volume data from structured, unstructured and semi-structured sources, and multi-dimensional datasets with a variety of tools
• Identify and assess information, data needs and requirements to support business plans / practices and business goals / objectives
• Use creative thinking and propose innovative ways as it relates to data mining, behavioural economics, statistics and statistical models, algorithms, data integration, information management, predictive analytics and analytics modeling, and data-related information technology

General Skills - 10%

• Communication skills to prepare technical and non-technical status reports, planning documents, and operational policies, and provide explanations on data issues and complex data analyses
• Writing skills to prepare technical specifications, source to target mapping document and data process flow diagrams
• Demonstrate experience working in a multi-team environment spanning across business and IT stakeholders in the pursuit of common missions, vision, values, and mutual goals.

MUST HAVES -

• Demonstrate knowledge of information management, data management, financial and business analysis, database architecture, and data related concepts such as data preparation, data integration, data anonymization, data extract / transform / load (ETL), data warehousing, data lineage, metadata management, master data management, and data governance
• Demonstrate knowledge of data skills, methods, techniques, and tools, including data mining, statistical analysis, statistical models and algorithms on machine learning, deep learning, natural language processing, artificial intelligence and other related disciplines
• Ability to analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)
• Manipulate and analyze complex, high-volume data from structured, unstructured and semi-structured sources, and multi-dimensional datasets with a variety of tools
• Identify and assess information, data needs and requirements to support business plans / practices and business goals / objectives