Sr. Data Scientist
Toronto, Ontario, Canada
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingB3 enables enterprise manufacturers to digitize their operations and use AI to improve performance.
In this role, you will own client engagements from end to end, starting from raw and often messy plant data and finishing with validated findings and working models.
In this role, you will own client engagements from end to end, starting from raw and often messy plant data and finishing with validated findings and working models.
From the employer’s posting
B3 enables enterprise manufacturers to digitize their operations and use AI to improve performance. Our AI & Data Science team builds the models, monitors, and AI features behind the platform, and a growing share of our work comes from client engagements: taking a manufacturer's raw operational data and turning it into insights and models they can act on.
In this role, you will own client engagements from end to end, starting from raw and often messy plant data and finishing with validated findings and working models. The data is industrial; time-series, sensor readings, downtime events, and shift reports and the audience is demanding in the best way: operators and plant managers who know their numbers well and will verify yours. We hold our work to that standard.
B3 enables enterprise manufacturers to digitize their operations and use AI to improve performance. Our AI & Data Science team builds the models, monitors, and AI features behind the platform, and a growing share of our work comes from client engagements: taking a manufacturer's raw operational data and turning it into insights and models they can act on. In this role, you will own client engagements from end to end, starting from raw and often messy plant data and finishing with validated findings and working models. The data is industrial; time-series, sensor readings, downtime events, and shift reports and the audience is demanding in the best way: operators and plant managers who know their numbers well and will verify yours. We hold our work to that standard. You will take project scoping and client goal setting conversations, and can grow into leading them over time. You will turn a well-scoped engagement into results the client can trust. The strongest of your work will graduate into our platform, where it serves clients beyond the one it was built for.
What you’ll bring
All qualificationsCore experience
- 4+ years of experience in data science or machine learning, including end-to-end ownership of projects you personally carried from messy source data to a delivered outcome.
- Experience with predictive maintenance, anomaly detection, or forecasting
- Strong Python skills and experience with the standard stack (pandas, scikit-learn, PyTorch or TensorFlow).
- Experience deploying models into production environments
- Degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.
- Familiarity with SQL and data pipelines
Preferred experience
- Experience with real-world, messy datasets; time-series, sensor, or event data is preferred.
Qualification wording
4+ years of experience in data science or machine learning, including end-to-end ownership of projects you personally carried from messy source data to a delivered outcome.
Experience with predictive maintenance, anomaly detection, or forecasting
Strong Python skills and experience with the standard stack (pandas, scikit-learn, PyTorch or TensorFlow).
Experience deploying models into production environments
Degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.
Familiarity with SQL and data pipelines
Experience with real-world, messy datasets; time-series, sensor, or event data is preferred.
Tools in this posting
- Python
- SQL
- Azure
- pandas
- scikit-learn
- PyTorch
- TensorFlow
Source — Tool mentions in context
- Comfortable working with stakeholders when the work calls for it: presenting findings clearly and asking good questions of the people who know the data best. - Strong Python skills and experience with the standard stack (pandas, scikit-learn, PyTorch or TensorFlow). - A solid foundation in statistics, modeling, and model evaluation — you know when a result is real, and you can demonstrate why.
- Experience deploying models into production environments - Familiarity with SQL and data pipelines - Experience with Azure or cloud-based data platforms
- Familiarity with SQL and data pipelines - Experience with Azure or cloud-based data platforms - Understanding of industrial, manufacturing, or operational data
About B3systems
Own client engagements end to end: ingesting raw client data, auditing its quality, exploring it, engineering features, building and validating models, and delivering the results.
In the employer’s words · Read in context
Job description
Sr. Data Scientist
About the Role
B3 enables enterprise manufacturers to digitize their operations and use AI to improve performance. Our AI & Data Science team builds the models, monitors, and AI features behind the platform, and a growing share of our work comes from client engagements: taking a manufacturer's raw operational data and turning it into insights and models they can act on.
In this role, you will own client engagements from end to end, starting from raw and often messy plant data and finishing with validated findings and working models. The data is industrial; time-series, sensor readings, downtime events, and shift reports and the audience is demanding in the best way: operators and plant managers who know their numbers well and will verify yours. We hold our work to that standard.
You will take project scoping and client goal setting conversations, and can grow into leading them over time. You will turn a well-scoped engagement into results the client can trust. The strongest of your work will graduate into our platform, where it serves clients beyond the one it was built for.
About the Work
- Own client engagements end to end: ingesting raw client data, auditing its quality, exploring it, engineering features, building and validating models, and delivering the results.
- Produce consulting-grade deliverables: clear write-ups and presentations, validated numbers, and models whose limitations are stated honestly, so that a client's own experts can check and trust the results.
- Build models for industrial problems such as anomaly detection, early-warning and predictive-maintenance questions, and forecasting, working mostly with time-series and event data.
- Agree on success criteria with the client before a build starts, so deliverables are judged against expectations both sides own.
- Work with the team to bring proven models and tools into the platform, where they can serve multiple clients.
- No industrial background is required. Our domain has plenty of complex workflows and terminology, and genuine curiosity is what carries people through it — we will help with the rest.
About You
- 4+ years of experience in data science or machine learning, including end-to-end ownership of projects you personally carried from messy source data to a delivered outcome.
- Comfortable working with stakeholders when the work calls for it: presenting findings clearly and asking good questions of the people who know the data best.
- Strong Python skills and experience with the standard stack (pandas, scikit-learn, PyTorch or TensorFlow).
- A solid foundation in statistics, modeling, and model evaluation — you know when a result is real, and you can demonstrate why.
- Experience with real-world, messy datasets; time-series, sensor, or event data is preferred.
- Sound independent judgment: you work well in a small team, seeking input rather than direction.
- Degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field.
Bonus Points
- Experience with predictive maintenance, anomaly detection, or forecasting
- Experience deploying models into production environments
- Familiarity with SQL and data pipelines
- Experience with Azure or cloud-based data platforms
- Understanding of industrial, manufacturing, or operational data
- Experience leading stakeholder or client discovery, including scoping projects and defining goals and success criteria.
About the Office
- All In, In Office – Centrally located at the corner of Yonge & St. Clair, we show up together, every weekday. Face-to-face time fuels our culture, speed, and creativity.
- Built for Growth – We’re moving fast, keeping structure light, and rewarding people who take ownership and drive momentum.
If you’re driven by applied AI, enjoy working in the future, and want to build data science solutions that make a real impact, we’d love to meet you.
Note: This position reflects an existing vacancy. B3 Systems is proud to be an Equal Employment Opportunity employer. We truly appreciate your interest in joining our team. While we may not be able to connect with every applicant, we will reach out directly to those selected for next steps. No “artificial intelligence” tool will be used to screening, assessment or selection of applicants for this opportunity.
We celebrate diversity and are committed to creating an inclusive, supportive workplace where everyone can thrive. If you require any accommodations or support at any stage of the selection process, please let us know—we’re happy to help.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on b3systems.bamboohr.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Toronto, Ontario, Canada
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 30, 2026
- Recorded sightings
- 10
- Last seen by us
- Oct 4, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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