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Senior Data Science Manager Jobs in Calgary, AB (NOW HIRING)

Data Elephant Inc

Oracle Data Analyst

Calgary, AB · Remote

Senior Oracle Data Analyst - Contract We are seeking a senior Oracle Data Analyst to support a ... master data management practices. Although the new environment is intended to become the ...

TELUS

L3 Data Management (GCP)

Calgary, AB · On-site +1

You will also have the opportunity to grow your skills under the mentorship of senior team members ... Bachelor's degree in Computer Engineering, Computer Science, or a related field Join our team and ...

TELUS

Bilingual Senior Project Manager

Calgary, AB · On-site

Manage diverse, matrixed project teams (Business Analysts, Data Analysts, Clinical teams ... Bachelor's degree in Business, Computer Science, Healthcare, or a related field * Project ...

ALS

Junior Machine Learning Engineer

Calgary, AB

CA$80K - CA$95K/yr

Collaborate with senior AI engineers and data scientists to improve model performance, reliability, scalability, and maintainability. * Support cloud-based AI and ML development using platforms such ...

PwC

Manager Cyber Cloud Security and AI

Calgary, AB · Hybrid

CA$116K - CA$166K/yr

Liaise with senior leadership, clients, and partners to understand their AI security and data ... Relevant degree in Computer Science orother applicable degree. * Excellent written and verbal ...

Parsons

Environmental Data & GIS Specialist

Calgary, AB · On-site +1

Knowledge of natural sciences and the management of geospatial, analytical, and collected field data is an asset * Environmental science knowledge would be considered an asset This position is part ...

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Senior Data Science Manager information

How does a senior data science manager typically collaborate with cross-functional teams to drive business outcomes?

A Senior Data Science Manager often works closely with stakeholders from product, engineering, marketing, and business operations to align data-driven initiatives with organizational goals. They are responsible for translating complex analytical findings into actionable insights and ensuring that data science projects address real business needs. Effective collaboration requires strong communication skills, the ability to prioritize multiple projects, and fostering a culture of knowledge sharing across teams. By coordinating with various departments, Senior Data Science Managers help ensure that data-driven strategies lead to measurable business impact.

What does a senior data science manager do?

A Senior Data Science Manager leads a team of data scientists to develop analytical solutions that drive business decisions and strategy. They oversee the end-to-end process of data collection, model development, and deployment, ensuring projects align with organizational goals. Additionally, they mentor team members, collaborate with stakeholders across departments, and help set the vision for data-driven initiatives. Their role requires both technical expertise and strong leadership skills.

What are the key skills and qualifications needed to thrive as a senior data science manager, and why are they important?

To thrive as a Senior Data Science Manager, you need strong expertise in data analysis, statistical modeling, and machine learning, typically supported by an advanced degree in a quantitative field and significant experience leading data teams. Familiarity with tools such as Python, R, SQL, cloud platforms (e.g., AWS, Azure), and data visualization software is essential, along with knowledge of project management methodologies. Outstanding leadership, communication, and strategic thinking skills are crucial for aligning data initiatives with business goals and fostering team development. These abilities are vital for driving impactful analytics projects, delivering actionable insights, and ensuring the success of data-driven strategies within an organization.

What is the difference between Senior Data Science Manager vs Data Scientist?

AspectSenior Data Science ManagerData Scientist
CredentialsAdvanced degree (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentLeads teams, manages projects, strategic planningAnalyzes data, builds models, reports findings
Employer & Industry UsageUsed in organizations with data teams, tech, finance, healthcareEntry to mid-level roles across industries

The main difference is that a Senior Data Science Manager oversees data teams and strategic initiatives, while a Data Scientist focuses on analyzing data and building models. The manager role involves leadership and project management, whereas the Data Scientist role is more technical and hands-on.

What cities near Calgary, AB are hiring for Senior Data Science Manager jobs? Cities near Calgary, AB with the most Senior Data Science Manager job openings:
Senior Data Science Manager jobs near you

Oracle Data Analyst

Data Elephant Inc

Calgary, AB • Remote

Contractor

Posted 7 days ago

Job description

Senior Oracle Data Analyst - Contract

We are seeking a senior Oracle Data Analyst to support a major application and database modernization initiative within the oil and gas sector. This is an initial 4-6-month contract focused on analyzing and resolving significant data discrepancies between a legacy Oracle application and its newly rebuilt replacement.


The organization is migrating data from multiple source systems into a new Oracle database while improving data transformation, prioritization, and master data management practices. Although the new environment is intended to become the authoritative source, millions of records currently do not align with the legacy system. The immediate priority is understanding why these differences exist and determining how the data should be populated.

This role is primarily analytical rather than development-focused. You will investigate data, trace legacy business rules, review SQL and PL/SQL logic, and identify whether discrepancies are caused by source data, data quality issues, transformation logic, field-mapping rules, or differences between the old and new applications.


Key responsibilities

  • Compare and reconcile large datasets across legacy and new Oracle databases.
  • Investigate approximately 7-10 million identified data discrepancies.
  • Perform detailed root-cause analysis to determine why records and fields do not match.
  • Review Oracle SQL, PL/SQL, stored procedures, and legacy application logic.
  • Trace data from multiple source systems through Informatica and PL/SQL transformations.
  • Determine the intended business rules and how individual fields should be populated.
  • Distinguish between source-data issues, transformation defects, mapping gaps, and logic differences.
  • Document findings, business rules, discrepancy patterns, and recommended resolutions.
  • Work closely with business stakeholders to validate data expectations.
  • Collaborate with architects and developers to recommend fixes that will not negatively affect other processes.
  • Support developers during remediation and validate that implemented fixes resolve the underlying issues.
  • Use AI-assisted analysis tools, where appropriate, to accelerate code review and discrepancy investigation.
  • Work independently, take ownership of assigned analysis, and communicate findings clearly to technical and business audiences.


Required qualifications

  • At least seven years of experience in data analysis, data migration, data quality, database development, or a closely related field.
  • Strong hands-on expertise with Oracle databases, Oracle SQL, and PL/SQL.
  • Demonstrated experience with large-scale data reconciliation, validation, and root-cause analysis.
  • Ability to read and understand existing database code, stored procedures, transformations, and business logic.
  • Experience investigating discrepancies between legacy and modernized systems.
  • Good understanding of ETL processes, relational databases, data warehousing, and data integration.
  • Experience translating technical findings into clear, business-friendly language.
  • Strong analytical skills, attention to detail, and a structured approach to problem-solving.
  • Ability to work with limited direction and take ownership of deliverables.
  • Previous oil and gas industry experience.


Preferred qualifications

  • Experience with Informatica.
  • Exposure to master data management and data governance.
  • Experience working with data originating from multiple operational source systems.
  • Backend application development experience.
  • Familiarity with AI tools such as GitHub Copilot or similar tools for SQL, code, and data analysis.
  • Advanced Excel skills.
  • Experience working within Agile delivery teams.


Contract details

  • Initial duration: 4-6 months
  • Work arrangement: Remote work is acceptable; alignment with the client's working time zone is preferred (MST)
  • Primary focus: Data analysis, reconciliation, and root-cause investigation
  • Industry: Oil and gas



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