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RQ07955 - Sr. Data Analytical Specialist/Scientist

Rubicon Path

Toronto

On-site

CAD 80,000 - 110,000

Full time

25 days ago

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Job summary

A leading analytics firm in Toronto is seeking an experienced Sr. Data Analytical Specialist/Scientist to lead analytics initiatives and support decision-making with actionable insights. The ideal candidate will have strong SQL and programming skills, experience in data mining, and a solid understanding of statistical models. This role offers a competitive salary and opportunities for professional development.

Benefits

Professional development opportunities
Health benefits
Flexible work environment

Qualifications

  • Proficient in SQL for data access and manipulation.
  • Experience with data mining and predictive analytics.
  • Strong analytical skills to identify data quality issues.

Responsibilities

  • Lead development of analytics to support evidence-based decision-making.
  • Gather requirements and identify opportunities for improvement.
  • Communicate analysis results clearly to stakeholders.

Skills

Structured Query Language (SQL)
Data mining
Statistical analysis
Machine learning
Analytical skills

Education

Bachelor’s degree in a related field

Tools

R
Python
PowerBI
Excel
Job description
RQ07955 - Sr. Data Analytical Specialist/Scientist

Job Openings RQ07955 - Sr. Data Analytical Specialist/Scientist

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

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 as R, PowerPivot, Matlab, SPSS, or SAS an asset

Proficiency with desktop analysis software including Microsoft Excel, Access, VBA

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
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