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Internship Machine Learning Quant Jobs in Alberta

... how to leverage machine learning capabilities to solve real user problems. * Execution and ... You are a visionary who uses both qualitative and quantitative data to drive product strategy ...

Bring a great attitude toward learning the business and local marketplace. Attend local business ... What you'll bring * 1+ years of relevant sales experience, quality internship experience is ...

Bring a great attitude toward learning the business and local marketplace. Attend local business ... What you'll bring * 1+ years of relevant sales experience, quality internship experience is ...

Loader Operator

Calgary, AB · On-site

CA$35.82/hr

Physically fit with stamina to operate machinery in various weather conditions and extended hours ... Access to online learning platforms, financial educational assistance, and a culture that fosters ...

Showing results 21-31

Internship Machine Learning Quant information

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

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For Internship Machine Learning Quant jobs in Alberta, the most frequently searched job titles are:

What job categories do people searching Internship Machine Learning Quant jobs in Alberta look for?

The top searched job categories for Internship Machine Learning Quant jobs in Alberta are:

What cities in Alberta are hiring for Internship Machine Learning Quant jobs?

Cities in Alberta with the most Internship Machine Learning Quant job openings:

Infographic showing various Internship Machine Learning Quant job openings in Alberta as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Databricks Solution Architect

Bits In Glass

Calgary, AB • Remote

Full-time

Posted 19 days ago


Job description

Databricks Solution Architect

Bits In Glass Remote-friendly (Canada)


Bits In Glass (BIG) is a high-growth AI and automation consulting firm with offices across Canada, the United States, India, and the United Kingdom. Our portfolio spans more than 10 leading technologies across AI, cloud, data, automation, and business applications.

Recognized globally as a Great Place to Work and the recipient of multiple partner excellence awards, BIG is built on collaboration, innovation, and delivering measurable business outcomes for enterprise clients. We are a team of experienced technology professionals who enjoy solving complex challenges, celebrating wins together, and helping customers modernize with confidence.

About the Role

We are looking for a hands-on Databricks Solution Architect to design the data and AI platforms that power our enterprise clients. This is a deeply technical role for an architect who wants to stay close to the technology - shaping Lakehouse architectures, building working prototypes, and setting the technical direction that delivery teams carry forward.

You will work directly with prospects and customers to understand their data challenges and design solutions on the Databricks Lakehouse Platform that actually fit their environment. That means partnering with our account and delivery teams throughout the sales process, ensuring the architecture you propose gets built. This role is ideal for someone who enjoys solving hard data problems, solution storytelling, and being the trusted technical voice customers rely on.

What You'll Do

  • Design scalable Databricks solution architectures - Lakehouse, Delta Lake, and Unity Catalog patterns - tailored to each customer's environment and business goals.
  • Lead technical discovery workshops to understand customer business objectives, data challenges, and current-state architecture
  • Build working prototypes, proofs-of-concept, and reference architectures that showcase the capabilities of the Databricks Lakehouse Platform.
  • Guide customers on best practices for data pipelines, data modeling, and platform governance.
  • Advise on integrating Databricks with hyperscaler environments (AWS, Azure, GCP) and adjacent data tooling.
  • Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI use cases, including Mosaic AI, MLflow, and Feature Store.
  • Identify and mitigate technical risks early so delivery teams are set up for success.
  • Translate complex technical concepts into clear business value for both technical stakeholders and executive audiences.
  • Partner with account teams throughout the sales process - from early prospect conversations through evaluation - to shape sound, winning technical strategies
  • Collaborate with Data Scientists and ML Engineers to develop AI-powered demo assets and reference architectures.

Technical Leadership & Community

  • Serve as a resident Databricks expert within BIG - sharing knowledge and enabling the broader team.
  • Contribute reusable accelerators, demo assets, and technical playbooks.
  • Stay current on Databricks platform releases and evolving data and AI patterns.
  • Represent BIG at customer events, webinars, and Databricks partner activities.
  • Provide field feedback to Databricks product and partner teams to help influence the roadmap.
  • Travel up to 15% for customer meetings and partner collaboration.

What You Bring

  • 3+ years of hands-on experience with Databricks and/or Snowflake in a technical capacity.
  • 5+ years in customer-facing technical roles - solutions architecture, technical consulting, or sales engineering.
  • Experience designing, presenting, and delivering production data architectures for enterprise customers - including Lakehouse, Delta Lake, and Unity Catalog Patterns - on AWS, Azure, and/or GCP.
  • Databricks Professional-level certification (e.g., Data Engineer Professional, Machine Learning Professional).
  • Strong expertise in at least one core data domain: big data engineering (Spark, Kafka), Data Warehousing & ETL, or Data Science & ML.
  • Fluency in Python and SQL (Scala, Java, or R is a plus).
  • Exceptional verbal and written communication and presentation skills - able to engage in and lead business-level meetings with technical and non-technical Client and internal team members.
  • Ability to translate complex topics into clear business value and earn buy-in from engineers and executives.

Nice to Have

  • A degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative field.
  • Experience with adjacent technologies such as dbt, Fivetran, Airflow, or Delta Sharing.
  • Familiarity with AI/GenAI frameworks and LLM application patterns.
  • Databricks GenAI Engineer Associate certification.
  • Exposure to enterprise engagement cycles and how technical decisions shape deal outcomes.
  • Experience with Frontier LLMs such as Claude code for SDLC acceleration.

Why Bits In Glass?

  • Work on meaningful, high-impact data and AI projects for enterprise clients across Canada, the US, UK, and India.
  • Join a Certified Great Place to Work with a people-first, collaborative culture.
  • Access to 10+ cutting-edge technology practices and continuous learning opportunities.
  • Competitive compensation, benefits, and a team that celebrates wins together.
  • Flexible, remote-friendly work environment.