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Added 39 mins ago
T
Research Machine Learning Scientist II
TD
Toronto, ON
- Full-time
Conduct internal and external research projects; support the development/ delivery of presentations / communications to management or broader audience.
Added 20 hours ago
W
Machine Learning Scientist I
Wayfair
Toronto, ON
- $132,440 to $145,684 CAD / year
- Full-time
…Engineering, Computer Science, Statistics/Biostatistics, Economics, Physics, Robotics, Operations Research, etc.) or Bachelor's degree in a quantitative field + 1+ years of…
Added 22 hours ago
OL
Research Scientist
OTI Lumionics Inc.
Mississauga, ON
- Full-time
Perform literature review on research projects
Added 1 day ago
Staff Research Scientist (AI for Self-Driving Labs, 2-year Term)
University of Toronto
Toronto, ON
…The AC develops self-driving laboratories (SDLs), autonomous research platforms that integrate artificial intelligence, robotics, automation, and advanced computing to dramatically reduce…
Added 2 days ago
NQ
research scientist, physics
Nord Quantique
Sherbrooke, QC
- Full-time
Design and conduct research in experimental and theoretical physics
Added 3 days ago
W
Machine Learning Scientist I
Wayfair
Toronto, ON
- $132,440 to $145,684 CAD / year
- Full-time
…Engineering, Computer Science, Statistics/Biostatistics, Economics, Physics, Robotics, Operations Research, etc.) or Bachelor's degree in a quantitative field + 1+ years of…
Added 3 days ago
TU
Black Faculty Position – Faculty of Science at the University of British Columbia, Vancouver – Assistant Professor
The University of British Columbia
Vancouver, BC
- Full-time
…computer science, ecology, fisheries, mathematics, oceanography, physics, statistics, zoology, or related disciplines. The candidate should be a creative, innovative scientist, with…
Added 3 days ago
Staff Applied Scientist
Upstart
Canada
As an Applied Scientist, you will research and implement enhancements to Upstart’s core unsecured underwriting model. Your work will directly influence credit decisioning and help the team…
Added 3 days ago
S
Data Scientist - Applied AI/Gen AI
Sanofi
Toronto, ON
- Full-time
You are a dynamic data scientist interested in challenging the status quo to ensure development and impact of Sanofi's AI solutions for the patients of tomorrow. You are an influencer and…
Added 3 days ago
UO
Black Faculty Position – Faculty of Science at the University of British Columbia, Vancouver – Assistant Professor
University of British Columbia
Vancouver, BC · UBCV | Earth Sciences Building (ESB)
- Full-time
…computer science, ecology, fisheries, mathematics, oceanography, physics, statistics, zoology, or related disciplines. The candidate should be a creative, innovative scientist, with…
Added 4 days ago
M
Senior Data Scientist
Mphasis
Calgary, AB
- Full-time
Education and background: a quantitative degree - statistics, computer science, engineering, operations research, economics, mathematics, physics, or similar. A master’s is preferred. A PhD…
Added 4 days ago
M
Research Scientist – Computer Vision (Body Pose Detection)v1
Mecka.ai
Richmond Hill, ON
- $150,000 to $200,000 USD / year
- Full-time
…human locomotion, and human-scene interaction. We are hiring a Research Scientist to architect and train proprietary foundation models from scratch focused on 3D human body tracking and…
Added 4 days ago
O
Staff Data Scientist - Wildfire
Overstory
Canada
- Full-time
We are excited to add a Staff Data Scientist, Wildfire to our team. This individual will lead the scientific foundation of our Fuel Detection Model, the core engine that translates…
Added 4 days ago
M
Lead Data Scientist
Mastercard
Toronto, ON
- Full-time
We are seeking a highly skilled and motivated Lead Data Scientist to join our Cyber Analytics team within the Security Solutions Data Science organization. The successful candidate will…
Added 4 days ago
S
Senior AI Machine Learning Engineer
SAP
Montreal, QC
- Full-time
We are hiring a Senior Machine Learning Engineer Scientist to lead the development of scalable graph-based and transformer-based modeling systems, along with production-grade ML pipelines.…
Added 4 days ago
OO
Engineering scientist
OZ Optics Ltd.
Ottawa, ON
- Full-time
Carry out applied research in fields of electrical and electronic engineering and physics
Added 5 days ago
M
Research Scientist – Computer Vision (Body Pose Detection)v1
Mecka
Richmond Hill, ON
- $150,000 to $200,000 USD / year
- Full-time
…human locomotion, and human-scene interaction. We are hiring a Research Scientist to architect and train proprietary foundation models from scratch focused on 3D human body tracking and…
Added 5 days ago
M
AI Software Engineer
Mphasis
Calgary, AB
- Full-time
Job Title: Applied AI ScientistDesignation: AI Scientist
Added 5 days ago
E
Sr. Data Scientist
Eneon-ES
Toronto, ON · Greater Toronto and Hamilton Area, ON
- Full-time
The Sr. Data Scientist will be responsible for transforming Eneon’s operational telemetry into reliable, actionable data systems that support decision-making across the company. As Eneon’s…
Added 6 days ago
B
Scientifique II, Opérations Scientifiques
BD
Quebec, QC · CAN Québec - GeneOhm Sciences
- Full-time
…harnesses deep scientific expertise across biology, chemistry, and physics. Waters collaborates with analytical laboratories around the world to advance the release of effective,…
Added 6 days ago
S
Lead Data Scientist
Sixone
Burnaby, BC
- $100,000 to $140,000 CAD / year
- Full-time
4+ years in data science or applied ML research with a focus on computer vision or spectral/sensor data
Added 6 days ago
T
Applied Machine Learning Scientist II
TD
Toronto, ON
- Full-time
Conduct internal and external research projects; support the development/ delivery of presentations / communications to management or broader audience.
Added 6 days ago
T
Senior Applied Machine Learning Scientist (predictive analytics)
TD
Toronto, ON · Montreal, QC
- Full-time
As a Senior Applied Machine Learning Scientist, you will lead a high-performing team of AI/ML professionals and provide technical leadership across the AI function. You will be responsible…
Added 6 days ago
G
Data Scientist
GHGSat
Montreal, QC
- Full-time
…visualize and quantify their emissions. We are looking for a data scientist to join the Science and Systems team. You will focus on applying computer vision and machine learning techniques…
Added 6 days ago
G
Data Scientist
GHGSAT
Montreal, QC
- Full-time
…visualize and quantify their emissions. We are looking for a data scientist to join the Science and Systems team. You will focus on applying computer vision and machine learning techniques…

Mphasis

Senior Data Scientist

Calgary, AB, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 15, 2026
Experience: Experience: 4+ years of applied data science delivery
Posting language: English
Posted: Oct 16, 2026

Original job description

Job Title: Senior Data Scientist

Location: Canada or United States (US time zones)

Experience: 4+ years of applied data science delivery

About The Role

You will work as a forward deployed data scientist: embedded with enterprise clients, turning ambiguous business problems into working analytical and AI solutions, and staying with the work until it runs in their environment. This is a hands-on senior role. You will own problems end to end - scoping with stakeholders, wrangling messy client data, choosing methods that fit the constraints, building the solution, and handing it off in a state another team can operate.

Some engagements need something built from scratch. Many do not - the work is adopting, configuring and extending what already exists: our own products and accelerators, the client’s current platform, or a vendor tool. We are looking for people who are comfortable either way, who can tell which situation they are in, and who would rather extend a working solution than rebuild it.

We are looking for modern technical builders rather than notebook-only analysts: fluent with Python, SQL, Git, cloud and cloud data platforms, AI-native in how they work, credible in front of a client, and pragmatic about when a simple method is enough and when deeper modelling is warranted.

Education and background: a quantitative degree - statistics, computer science, engineering, operations research, economics, mathematics, physics, or similar. A master’s is preferred. A PhD is welcome but not expected. A strong bachelor’s candidate is equally of interest where there is clear evidence of applied delivery.

What You Will Do

Partner directly with client stakeholders to translate business problems into analytical problems - and push back when the framing is wrong.
Build reliable analytical assets on messy enterprise data: forecasting, optimization, ML, statistical models, and the pipelines around them.
Just as often, work with what is already there - configure and extend our existing products and accelerators, or the client’s existing tools, rather than rebuilding from scratch.
Put something in a stakeholder’s hands early - a prototype app, a dashboard, a clear analysis - and iterate from real feedback.
Ship code others can reuse: tested, documented, reproducible, reviewed.
Work alongside data engineers and ML engineers through to deployment, rather than throwing work over the wall.
Use LLMs and AI coding tools to move faster, while keeping statistical judgment and final review your own.
Raise the level of the people around you: review work and mentor less experienced colleagues.

Required

Engineering and tooling

Strong proficiency in Python and SQL, at a level where your code goes to other people rather than only into your own notebook.
Comfortable with Git, pull requests, code review, terminal workflows, package management, and reproducible environments.
Working experience on at least one major cloud (AWS, Azure, or GCP) and with a modern data platform such as Snowflake, Databricks, BigQuery, Redshift, Spark, or equivalent.
Able to turn exploratory analysis into reusable, tested, and documented code.
Comfortable working inside an existing codebase or product as well as starting from a blank page - reading someone else’s code, understanding how it works, and extending it without breaking it.
Able to independently troubleshoot common data, query, environment, and pipeline issues - failed jobs, broken queries, bad joins, package conflicts, data-quality problems - without immediately requiring an engineer.

Data science

Strong practical data science skills, including working with messy enterprise data and translating business problems into actionable analysis.
Working knowledge of forecasting, optimization, machine learning, and statistical methods - with the judgment to know when a simple method is sufficient, and the discipline to validate honestly (proper backtesting and out-of-time validation for time series, not just a random train/test split).
Able to answer “did this actually work?” with defensible evidence: experiment design and read-out, or quasi-experimental methods when a clean test is not possible.
Regular user of LLMs or AI coding tools for coding, analysis, debugging, testing, and documentation, while maintaining independent judgment. You should be able to explain what AI output you accepted, rejected, rewrote, and tested, and how you spot output that is plausible but wrong.
Basic understanding of production data/ML concepts, including pipelines, data quality, reproducibility, versioning, deployment, and monitoring.

Delivery and client work

Able to take an ambiguous request from a business stakeholder and turn it into a scoped piece of work, with a view on what is feasible in the time available.
Able to clearly communicate assumptions, limitations, findings, and recommendations to both technical and business stakeholders - in writing and in the room.
Able to make results usable: a lightweight app or dashboard (for example Streamlit, Dash, Plotly, or a BI tool) or a clean, well-argued document, depending on what the audience needs.
Comfortable working in someone else’s environment and under their constraints - client tooling, access restrictions, and shifting priorities - without stalling.

Also an Asset

Strong engineering practices, experience with advanced LLM workflows, and experience delivering in enterprise environments are an asset.

About Mphasis

Mphasis applies next-generation technology to help enterprises transform businesses globally. Customer centricity is foundational to Mphasis and is reflected in the Mphasis’ Front2Back™ Transformation approach. Front2Back™ uses the exponential power of cloud and cognitive to provide hyper-personalized (C=X2C2™=1) digital experience to clients and their end customers. Mphasis’ Service Transformation approach helps ‘shrink the core’ through the application of digital technologies across legacy environments within an enterprise, enabling businesses to stay ahead in a changing world. Mphasis’ core reference architectures and tools, speed and innovation with domain expertise and specialization are key to building strong relationships with marquee clients.

Equal Opportunity Employer

Mphasis is an equal opportunity/affirmative action employer. We provide equal employment opportunities to applicants and existing associates and evaluate qualified candidates without regard to race, gender, national origin, ancestry, age, color, religious creed, marital status, genetic information, sexual orientation, gender identity, gender expression, sex (including pregnancy, breast feeding and related medical conditions), mental or physical disability, medical conditions military and veteran status or any other status or condition protected by applicable federal, state, or local laws, governmental regulations and executive orders. View the EEO in the law poster here, view the EEO in the law supplement here. To view the pay transparency nondiscrimination provision please click here and to view the E-Verify posting click here.

Mphasis is committed to providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of disability to search and apply for a career opportunity, please send an email to accomodationrequest@mphasis.com and let us know your contact information and the nature of your request.

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More about this job

Responsibilities

Partner with enterprise clients to scope ambiguous business problems and deliver practical analytical and AI solutions, from data preparation and modeling through deployment and handoff. Build and extend reusable, tested solutions, communicate findings to stakeholders, and mentor colleagues.

Requirements

Requires 4+ years of applied data science delivery, strong Python and SQL skills, experience with Git and at least one major cloud and modern data platform, and practical knowledge of forecasting, optimization, machine learning, and statistical methods. Candidates should be able to deliver end-to-end client work, communicate clearly with technical and business audiences, and use AI tools with independent judgment; a quantitative degree is expected, with a master's preferred.

Skills

Python
SQL
Git
Cloud Platforms
Cloud Data Platforms
Forecasting
Optimization
Machine Learning
Statistical Modeling
Experiment Design
LLMs
Data Pipelines
Data Quality
Production Deployment
Client Communication
Mentoring

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Git
AWS
Azure
GCP
Snowflake
Databricks
BigQuery
Redshift
Spark
Forecasting
Optimization
Machine Learning
Statistical Modeling
LLMs
AI Coding Tools
Data Pipelines
Data Quality
Backtesting
Out-of-Time Validation
Experiment Design
Quasi-Experimental Methods
Streamlit
Dash
Plotly
Business Intelligence
Enterprise Data
Production Deployment
Code Review

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