Lead Data Analytics Auditor Jobs

Hold at least one professional certification such as CIA, CISA, CAP, ACDA or any relevant certification related to data analytics/data science.

Demonstrate excellent oral and written communications in the English language, and excellent presentation and interpersonal skills.

Perform data gathering and data cleaning.

Perform statistical hypothesis and analysis of structured data and unstructured data to gain insights and detect anomalies.

Assist in the development of machine learning modelling and evaluation.

Assess effectiveness, performance and accuracy of data models.

Experience in the field of data analytics within SaaS is a plus working with Marketing, Sales, and Finance

Experience with data visualization tools such as Metabase, Looker, or similar platforms.

Excellent communication and presentation skills to convey complex technical concepts to non-technical stakeholders.

Strategic thinking and problem-solving abilities to identify data-driven opportunities and solutions for business challenges.

5+ years experience in data and analytics role

Expertise in data analysis, analytics engineering, and statistical modeling, with proficiency in programming languages like Python or R.

Minimum one year of supervisory and performance management experience

At least 5 years of progressive experience in business intelligence/data analytics, KPI development, metrics reporting, dash-boarding, and analyzing large datasets

Proven experience managing multiple project and meeting deadlines

A comprehensive benefits package including medical, dental, vision, and generous mental health support options – all available on day 1

Managing the Data and Analytics team of two

Gain a deep understanding of the business and market to help drive data driven decisions

Experience in the field of data analytics within SaaS is a plus working with Marketing, Sales, and Finance

Experience with data visualization tools such as Metabase, Looker, or similar platforms.

Excellent communication and presentation skills to convey complex technical concepts to non-technical stakeholders.

Strategic thinking and problem-solving abilities to identify data-driven opportunities and solutions for business challenges.

5+ years experience in data and analytics role

Expertise in data analysis, analytics engineering, and statistical modeling, with proficiency in programming languages like Python or R.

-Experience in Design, build and configure Snowflake DWH to meet business process and application requirements.

-Experience and knowledge of Salesforce.com - custom Lightning and Apex development is a plus

-Skills Experience in BioTech/Pharmaceutical industries desirable though not required

-Hands-on experience in writing AWS Lambda, Glue, EMR, Python, and Spark jobs.

-Hands on experience building dashboards using Qlik or Tableau and self service tools like ThoughtSpot

-Candidate should have good experience with Data pipeline, data manipulation and data visualization.

We support a hybrid work environment consisting of in-person collaboration at our Calgary office and flexible remote work.

Post-secondary degree in Computer Science, Statistics or related technical discipline, or equivalent industry experience.

8+ years’ data / analytics / business intelligence experience in a professional environment.

Proven experience in design, architecture, implementation, and operation of large, scalable analytical solutions.

Excellent communication and facilitation skills, with the ability to build relationships and collaborate effectively with cross-functional teams.

Strong problem-solving skills and the ability to think critically and strategically, with a data-driven mindset.

Hold at least one professional certification such as CIA, CISA, CAP, ACDA or any relevant certification related to data analytics/data science.

Demonstrate excellent oral and written communications in the English language, and excellent presentation and interpersonal skills.

Perform data gathering and data cleaning.

Perform statistical hypothesis and analysis of structured data and unstructured data to gain insights and detect anomalies.

Assist in the development of machine learning modelling and evaluation.

Assess effectiveness, performance and accuracy of data models.