Posted 3 months ago
Data Science & Data Engineering Intern – Quote Intelligence
@ EndeavourOn
St. John's, Newfoundland and Labrador
SIGNALS
Overview
EndeavourOn is hiring a part-time data science or data engineering intern, enrolled in a Master's program, in Saint John, NB. The intern builds pipelines on historical quote data and develops AI models that adjust pricing for market fluctuation and flag low-margin quotes. The posting requires Python, SQL and machine learning fundamentals.
Responsibilities:
- Collect, clean and structure historical quote data
- Build and maintain Python data pipelines
- Develop and test AI/ML models for market fluctuation in pricing
- Build guardrails flagging quotes below margin thresholds
- Present findings to technical and non-technical stakeholders
Requirements summary:
- Enrolled in a Master's program in a related field
- Strong Python skills with pandas, NumPy and scikit-learn
- Solid SQL and relational data modelling
- Machine learning fundamentals including regression and time series
- Legally eligible to work in Canada
Tools & skills
Source and dates
Source type not verified · apify-linkedin
- Employer posting date
- 2026-08-19
- First seen by our source
- 2026-11-15
- Source record updated
- 2026-11-15
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Entry level |
| Department | Data & analytics |
| Travel | air: none · ground: none |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Master’s degree (required) |
| Fields of study | Data Science, Data Engineering, Analytics, Computer Science |
Summary and details written by AI from the posting; the employer’s posting is the authority.
EndeavourOn
| Field | Value |
|---|---|
| Open jobs on Jobsy | 1 |
Job description
EndeavourOn is looking for a Master’s student in Data Science or Data Engineering to join us in Saint John, NB, for a hands-on internship at the intersection of data engineering and applied AI.
Quoting is where margin is won or lost. Our quoting tool produces the pricing that eventually becomes an invoice — and when raw material costs, supplier rates, or market conditions shift between the quote and the invoice, margin quietly erodes. Your job is to help us see that coming and correct for it.
You’ll work with years of historical quote data, build the pipelines that make it usable, and help develop AI models that adjust pricing for market fluctuation so that no quote leaves the door undervalued.
What you’ll do
Quoting is where margin is won or lost. Our quoting tool produces the pricing that eventually becomes an invoice — and when raw material costs, supplier rates, or market conditions shift between the quote and the invoice, margin quietly erodes. Your job is to help us see that coming and correct for it.
You’ll work with years of historical quote data, build the pipelines that make it usable, and help develop AI models that adjust pricing for market fluctuation so that no quote leaves the door undervalued.
What you’ll do
- Collect, clean, and structure historical business quote data — pricing, cost inputs, margins, win/loss outcomes, and customer segments.
- Build and maintain Python data pipelines in PyCharm, with an emphasis on reproducibility, version control, and clear documentation.
- Explore the data for the patterns that matter: where margin compresses, which quote types are most exposed to cost volatility, and how pricing drifts between quote and invoice.
- Develop and test AI/ML models that account for market fluctuation in price and cost inputs, and translate those signals into pricing and margin adjustments inside the quoting tool.
- Build guardrails that flag quotes falling below acceptable margin thresholds before they’re issued, so generated invoices reflect true business value.
- Validate model output against historical results and work with our commercial team to sanity-check recommendations against real-world judgment.
- Present findings and recommendations to both technical and non-technical stakeholders.
- Currently enrolled in a Master’s program in Data Science, Data Engineering, Analytics, Computer Science, or a related field.
- Strong Python skills, with practical experience in PyCharm and libraries such as pandas, NumPy, and scikit-learn.
- Solid grounding in SQL and relational data modelling.
- Experience with machine learning fundamentals — regression, time series forecasting, model evaluation, and the discipline to know when a model shouldn’t be trusted.
- Comfort working with messy, incomplete, real-world business data.
- Clear communication skills, and genuine curiosity about the business problem behind the numbers.
- Legally eligible to work in Canada for the duration of the internship.
- Exposure to pricing analytics, margin analysis, quoting/CPQ systems, or ERP data.
- Familiarity with time series forecasting for cost or commodity indices.
- Experience with version control (Git), cloud data platforms, or workflow orchestration tools.
- Interest in the practical side of AI — models that get used, not just models that get published.
- Ownership of a defined, measurable problem with visible impact on the business.
- Mentorship from our data and commercial teams.
- Exposure to the full lifecycle: raw data → pipeline → model → production decision.
- Experience that maps directly onto a thesis, capstone, or research project.
Journal
Only you can see this. Kept on this device, and in your account when you sign in.