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

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

Key responsibilities for this role include, but are not limited to the following:

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

Analyze data in source systems to identify data quality issues (e.g., missing values, duplicate meanings, and invalid data)

Develop complex SQL queries to extract, analyse and validate key business data from a wide range of data repositories (relational and multi-dimensional data stores (Oracle and MS SQL Server), flat files, structure and unstructured)

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

Provide planning advice to the project team on the use of data, and building capacity within the Ministry on performing advanced analytics and data analysis;

Provide advise and guidance to the project team on data de-identification to minimize privacy risks

Creating and/or updating data processing overview, technical design, source to target mapping, operation manual and other technical documentation;

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

Originally posted on Himalayas

RQ07955 - Sr. Data Analytical Specialist/Scientist

Job Description