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Data Science Jobs in Alberta (NOW HIRING)

Viridien

Machine Learning Engineer

Calgary, AB · On-site

Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity ...

Clio

Data Architect

Calgary, AB · Hybrid

CA$128K - CA$147K/yr

You'll turn raw product and business data (structured and unstructured) into high-quality, documented, and governed datasets and a semantic layer that enables analysts, data scientists, and AI agents ...

Fullscript

Senior Data Engineer

Calgary, AB · Remote

CA$11K - CA$140K/yr

Collaborate with data science and product partners to ensure data models support causal inference and predictive analysis needs * Optimize pipeline performance and scalability in cloud data ...

Targeted Talent

C++ Developer

Calgary, AB · On-site +1

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Apply Early

Targeted Talent

C++ Developer

Calgary, AB · On-site +1

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Apply Early

Targeted Talent

C++ Developer

Edmonton, AB · On-site +1

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Apply Early

Targeted Talent

C++ Developer

Edmonton, AB · On-site +1

Proficient with python data-science libraries ( pandas, numpy, bokeh ) * Expertise in combinatorial and graph optimization algorithms * A Masters or PHD in Computer Science, Engineering. or ...

Apply Early

Targeted Talent

R Developer

Calgary, AB · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Apply Early

Targeted Talent

R Developer

Calgary, AB · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Apply Early

Targeted Talent

R Developer

Edmonton, AB · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Apply Early

Targeted Talent

R Developer

Edmonton, AB · Remote

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Apply Early

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Showing results 1-20

All JobsData Science JobsData Science Jobs in Alberta

Data Science information

See Alberta salary details

$23.5K

$116.9K

$210.5K

How much do data science jobs pay per year?

As of Jul 4, 2026, the average yearly pay for data science in Alberta is $116,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $161,000.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Alberta? The most popular types of Data Science jobs in Alberta are:
What are popular job titles related to Data Science jobs in Alberta? For Data Science jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Alberta look for? The top searched job categories for Data Science jobs in Alberta are:
What cities in Alberta are hiring for Data Science jobs? Cities in Alberta with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Alberta as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $116,864 per year, or $56.2 per hour.
Data Migration & Automation Developer

Data Migration & Automation Developer

Modular Solutions

Calgary, AB

Full-time

Medical, Dental, Vision, PTO

Posted 6 days ago

Job description

About Modular Solutions

Founded in 2015, Modular Solutions delivers enterprise-grade technology to the insurance industry. Our configurable platform helps insurers, mutuals, MGAs, and brokers manage core operations through a single system designed for flexibility, long-term growth, and complex regulated environments.

Position Summary

Modular Solutions is seeking a Data Migration & Automation Developer to support client data migration, conversion, BI, and implementation projects. This developer-oriented role sits within our Data team and focuses on moving data from source platforms, files, spreadsheets, and custom systems into one clean target state in Modular's platform.


The ideal candidate is strong with SQL, ETL/ELT, BI, semantic models, scripting, data quality, and migration patterns. They should know how to clean, transform, validate, reconcile, and document data effectively while helping improve and extend our existing migration system.

Strong AI capability is a core requirement. We are looking for someone who understands modern AI-assisted and agentic development workflows and can apply them responsibly to migration and BI work, including source analysis, semantic modeling, report/data-model review, mapping, scripting, validation, documentation, and automation. This role is well suited for someone who enjoys working with data, solving technical problems, identifying inconsistencies, and collaborating with both technical and business teams.

Key Responsibilities

  • Support client data migration, conversion, BI, and implementation projects as a developer-oriented member of the Data team.
  • Extract, clean, transform, map, reconcile, and load data from multiple source platforms, spreadsheets, files, and custom systems into a single, consistent target model.
  • Analyze source data to identify gaps, inconsistencies, duplicates, missing relationships, formatting issues, and other data quality concerns.
  • Write and maintain SQL queries, scripts, migration utilities, data mapping documentation, conversion rules, validation logic, migration notes, and runbooks.
  • Improve and extend our existing migration system, including ETL/ELT patterns, conversion tools, templates, validation checks, semantic-model patterns, BI workflows, and quality-control processes.
  • Use AI-assisted and agentic development workflows to accelerate source analysis, semantic-model design, BI/reporting review, SQL/script generation, documentation, validation, and internal automation while maintaining strong human review.
  • Support test conversions, mock migrations, production migration activities, reporting, reconciliation, and post-migration validation against source systems, business requirements, and expected platform outcomes.
  • Collaborate with Data, Development, Product, Implementation, and business stakeholders to understand data requirements, clarify business rules, resolve defects or conversion gaps, and communicate progress, risks, and dependencies.

Required Qualifications

  • A degree, diploma, or certificate in Computer Science, Data Science, Software Development, Information Systems, or a related field, or equivalent professional experience.
  • 3+ years of experience with data migration, data conversion, BI/reporting, semantic models, ETL/ELT, database development, data analysis, implementation projects, or software development.
  • Strong SQL skills and experience with PostgreSQL and analytical data platforms such as Snowflake.
  • Strong understanding of data cleansing, transformation, mapping, validation, reconciliation, and migration from many source platforms and data formats into a clean, reusable target state.
  • Experience using scripting or programming languages such as C#, Python, PowerShell, TypeScript, or similar tools to automate data, reporting, semantic-layer, or migration workflows.
  • Hands-on experience with BI tooling, semantic models, governed metrics, reusable reporting models, and reporting assets that can be reviewed, versioned, tested, or automated.
  • Demonstrated experience with modern AI-assisted and agentic development workflows for coding, scripting, analysis, documentation, BI/reporting work, validation, or automation.
  • Strong analytical, communication, and problem-solving skills, with high attention to detail and the judgment to validate AI-generated code, SQL, mappings, summaries, and analysis before use in client-facing or production migration work.
  • Ability to read and interpret business rules, technical documentation, data layouts, and mapping specifications while managing competing priorities during migration projects.


Preferred Qualifications

  • Insurance data experience, especially policy, billing, claims, broker, customer, coverage, risk, or transaction data.
  • Experience converting data from insurance systems, policy administration systems, spreadsheets, custom-built tools, or other business data sources.
  • Experience with ETL/ELT tools, APIs, internal tooling, automation frameworks, BI tooling, semantic-model tooling, migration utilities, cloud-hosted environments, Agile delivery tools, or implementation/onboarding projects.
  • Snowflake experience is a major asset.
  • Power BI, Microsoft Fabric, or similar BI platform experience is a strong asset, especially where reports, models, and metrics are structured, reviewable, or source-controlled.
  • Experience using agents or automation to improve BI workflows, such as reviewing reporting logic, validating models, documenting semantic layers, or creating quality checks.

Our Technology Stack and Architecture:

Our core platform uses C#/.NET, Entity Framework, PostgreSQL, React, TypeScript, and Azure. This role works closely with product engineering teams on system logic, database structures, APIs, and platform requirements related to migration, BI, data quality, and automation workflows.

Why Join Modular Solutions?

We are building a long-term platform in a complex industry where customers depend on accurate data every day. You will help expand our migration system and make migration and BI work cleaner, faster, and more AI-enabled as we grow. We value autonomy, accountability, strong technical judgment, and people who take pride in building production-grade systems the right way.

What We Offer

  • Be part of a growing company building a modern, enterprise-grade platform for the insurance industry.
  • Work alongside experienced insurance and technology professionals in a collaborative environment.
  • Flexible remote work environment, with a preference for Alberta-based team members, and periodic in-person planning sessions and team events.
  • Extended health, dental, and vision benefits.
  • Access to an Employee and Family Assistance Program.
  • Annual professional development allowance.
  • Additional paid time off beyond standard statutory holidays and vacation.
  • Recognition for meaningful contributions and career milestones.
  • Share Appreciation Rights program so you participate in the company's long-term success.


To Apply:

Please submit your resume and a brief cover letter outlining your relevant experience and what excites you about this opportunity. We thank all applicants for their interest; only those selected for an interview will be contacted.

Apply