What are the job requirements for a Data Scientist in Ontario?

Typically, a Data Scientist job in Ontario requires a strong background in mathematics, statistics, or computer science. Employers often look for candidates with experience in data mining, machine learning, and programming skills in languages like Python, R, or SQL. Advanced degrees in data science or related fields are commonly preferred.

How can I find Data Scientist job openings in Ontario?

Job openings for Data Scientists in Ontario can be found on various online job boards, company websites, networking events, and through recruitment agencies specialized in tech roles. Popular online platforms like LinkedIn, Indeed, and Glassdoor frequently list data science job openings in the region.

What is the typical career progression for a Data Scientist in Ontario?

A Data Scientist in Ontario often begins as a junior or entry-level analyst, progressing to more senior data scientist roles. With experience, they may move into specialized positions like machine learning engineer or advanced analytics roles. Ultimately, they could become data science managers, lead teams, or transition into higher-level managerial roles focusing on strategy and business intelligence.

What factors affect Data Scientist salaries in Ontario?

Salaries for Data Scientists in Ontario are influenced by factors such as educational background, relevant experience, industry demand, the complexity of the role, size and type of company, and the cost of living in specific areas within Ontario. Expertise in specialized tools and the ability to manage large-scale data projects can also command higher salaries.

Data Scientist Salaries in Ontario

Lead Data Scientist Supply Chain<\/b><\/h2>
Mississauga, Canada<\/p>
Job ID JR0146090<\/p>
Category Data Scientist, Information Technology<\/p>
Post Date Apr. 20, 2026<\/p>
<\/div>
<\/div>
<\/p>

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve we care.<\/p>
What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrows health today, we want to hear from you.<\/p>

Job Title<\/b><\/h2>
Lead Data Scientist, Supply Chain Operations Research<\/b><\/p>
Summary<\/b><\/h2>
The Lead Data Scientist, Supply Chain Operations Research will architect and deliver advanced analytics, optimization, and AI\/ML solutions to improve the efficiency, resilience, and working capital performance of McKessons supply chain. This role sits within McKessons Supply Chain & Operations Center of Excellence (COE) and focuses on enterprise-scale inventory optimization, simulation, and decision science initiatives.<\/p>
What Youll Do<\/b><\/h2>

Lead the design and implementation of AI\/ML and operations research solutions to optimize enterprise inventory and supply chain systems<\/li>
Develop stochastic, statistical, and optimization models to support next-best-action decision-making across the supply chain network<\/li>
Design and enhance multi-echelon inventory optimization and simulation frameworks<\/li>
Contribute to the development of enterprise-scale digital twins to support inventory and working capital management<\/li>
advanced statistical simulation and decision frameworks to complex supply chain problems<\/li>
Support the development of AI\/ML-driven monitoring solutions that proactively identify inventory and working capital optimization opportunities<\/li>
Partner with stakeholders to translate business problems into analytical solutions and drive adoption of delivered products<\/li>
Communicate analytical insights and recommendations clearly to both technical and non-technical audiences<\/li>
Mentor and coach junior and developing data science team members<\/li>
Collaborate cross-functionally to identify new analytics use cases and support long-term analytics roadmap execution<\/li> <\/ul>
What You Bring<\/b><\/h2>

Strong expertise in operations research, optimization, and advanced statistical modeling<\/li>
Demonstrated experience applying AI\/ML techniques to large-scale, real-world supply chain or operations problems<\/li>
Proven ability to lead complex analytical initiatives from problem framing through implementation and adoption<\/li>
Ability to work across the full data lifecycle, from data exploration and modeling to scalable deployment and stakeholder consumption<\/li>
Strong communication skills, with the ability to explain complex technical concepts to diverse audiences<\/li> <\/ul>
Minimum Requirements<\/b><\/h2>

Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Masters or Doctorate qualifications.<\/li> <\/ul>
Preferable Skills & Experience<\/b><\/h2>

Experience with optimization solvers and toolkits such as CPLEX, Gurobi, XPress, or open-source solvers (e.g., CBC, GLPK)<\/li>
Demonstrated experience solving enterprise inventory optimization and\/or transportation optimization problems<\/li>
Strong foundation in statistical methods and techniques, including regression, probability distributions, hypothesis testing, and A\/B testing<\/li>
Proficiency in object-oriented programming languages such as Python, Java, C#, or similar<\/li>
Experience with statistical or analytical programming tools such as R, SAS, or MATLAB<\/li>
Strong SQL and data wrangling skills across relational databases (e.g., Snowflake, SQL Server, Oracle)<\/li>
Familiarity with cloud-based analytics platforms (Azure, AWS, GCP, Databricks)<\/li>
Experience with data warehousing, ETL processes, and analytics best practices<\/li>
Advanced Excel skills, including financial modeling and reporting<\/li>
Prior experience working with enterprise systems such as SAP or JD Edwards is a plus<\/li> <\/ul> <\/div>
We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson,
(opens in new window) <\/div> <\/div>
Our Base Pay Range for this position<\/b><\/p> $122,100 - $162,800
McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKessons (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.<\/p>
McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.<\/p>
McKesson job postings are posted on our career site: careers.mckesson.com
(opens in new window) <\/div> . <\/div>
McKesson is an Equal Opportunity Employer<\/b><\/p>
McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKessons full Equal Employment Opportunity policies, visit our Equal Employment Opportunity
(opens in new window) <\/div> page. <\/div>
McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com
(opens in new window) <\/div> or (Canada) Accessibility@mckesson.ca
(opens in new window) <\/div> . Resumes or CVs submitted to this email box will not be accepted. <\/div>
Join us at McKesson!<\/b><\/p> <\/div> <\/div>
<\/div><\/body><\/html>","company":"McKesson","city":"Mississauga","inferred_city":"Mississauga","inferred_city_with_inferred_state":"Ontario | Mississauga","inferred_cbsa":null,"fips":null,"is_metropolitan":null,"state":"ON","inferred_state":"Ontario","country":"Canada","inferred_country":"Canada","squirrel_codes":[]},"sort":[1776729600000]},{"_index":"job__1736258560_877903","_type":"_doc","_id":"205990510","_score":null,"_source":{"created":"2026-04-24T08:47:22.069490+00:00","unique_id":"2770b8d9-f699-564c-972e-e4e307767670","key":"46c4ac57cb2f4fd148569c22e3c611c3","title":"Data Scientist","inferred_title":"Data scientist","salary_offered":null,"inferred_salary_from":60,"inferred_salary_to":70,"inferred_salary_yearly_from":124800,"inferred_salary_yearly_average":135200,"inferred_salary_yearly_to":145600,"inferred_salary_yearly_range_spread":0.17,"inferred_salary_currency":"CAD","inferred_salary_time_unit":"hourly","inferred_max_experience":5,"inferred_average_experience":5,"inferred_min_experience":5,"inferred_seniority_level":"Mid Level","sign_on_bonus":null,"url":"https:\/\/ca.linkedin.com\/jobs\/view\/data-scientist-at-altis-technology-4403653798","type":"Contract","category":null,"board":"Linkedin","post_date":"2026-04-20","is_remote":false,"html_description":"
Job Title:<\/strong> Data Scientist, Health Modelling<\/p>
Location:<\/strong> Remote, Canada<\/p>
Job Type:<\/strong> Contract, 7.25 hour day<\/p>
Clearance:<\/strong> N\/A<\/p>
Language:<\/strong> Strong written and spoken English required, French is an asset<\/p>
Compensation:<\/strong> Open rate. Estimated: $60$70\/hour inc<\/p>
About the Opportunity<\/strong><\/p>
Our public sector client in the healthcare space is seeking a Data Scientist to support the development of advanced microsimulation models that inform critical health system planning decisions. This work focuses on modelling patient flow and care pathways, particularly for aging populations and individuals living with complex conditions such as dementia.<\/p>
Youll join a collaborative, interdisciplinary environment alongside researchers, clinicians, and policy experts, contributing to impactful, data-driven insights that shape healthcare delivery across Canada. This is an opportunity to work on meaningful, real-world problems where your models directly influence system capacity and patient outcomes.<\/p>
Whats in it for You<\/strong><\/p>
Youll gain exposure to high-impact health policy initiatives while working with modern simulation frameworks and diverse datasets. The team fosters a collaborative and knowledge-sharing culture, offering the chance to deepen your expertise in health analytics, modelling, and applied research.<\/p>
This is an ideal opportunity for someone who values purpose-driven work, continuous learning, and cross-functional collaboration in a remote-first environment.<\/p>
Your Responsibilities<\/strong><\/p>
Youll design and develop microsimulation models to represent patient care trajectories across healthcare systems<\/li>
In this role, youll apply simulation techniques such as discrete-event and agent-based modelling using Python or R<\/li>
Youll collaborate with multidisciplinary stakeholders to ensure models reflect real-world healthcare scenarios<\/li>
Youll conduct validation, calibration, and scenario analysis to assess system-level impacts<\/li>
Youll translate complex outputs into clear insights through reporting, visualizations, and presentations<\/li><\/ul>
Skills and Qualifications<\/strong><\/p>
5+ years of experience in data science, health analytics, or simulation modelling<\/li>
Strong programming skills in Python or R, with experience in simulation frameworks such as SimPy, Mesa, or OpenM++<\/li>
Experience with statistical modelling, sensitivity analysis, and model validation techniques<\/li>
Ability to communicate complex technical findings to both technical and non-technical audiences<\/li>
Experience working in healthcare, public sector, or research environments is an asset<\/li><\/ul>
Why Partner with Altis<\/strong><\/p>
If youve never worked with a staffing agency before, dont worry, we make it easy. Youll still engage directly with the client while we handle the logistics, provide guidance, and keep you informed every step of the way. Well represent your strengths, guide you through each stage of the process, and ensure the experience feels personal and transparent.<\/p><\/body><\/html>","company":"Altis Technology","city":"Toronto","inferred_city":"Toronto","inferred_city_with_inferred_state":"Ontario | Toronto","inferred_cbsa":null,"fips":null,"is_metropolitan":null,"state":"ON","inferred_state":"Ontario","country":"Canada","inferred_country":"Canada","squirrel_codes":[]},"sort":[1776643200000]},{"_index":"job__1736258560_877903","_type":"_doc","_id":"205989595","_score":null,"_source":{"created":"2026-04-24T08:47:22.069490+00:00","unique_id":"e55ad7a6-97e0-5967-bc74-bd036edd0c5d","key":"a348325fc116a327b054f9285d1dbd7f","title":"Data Scientist","inferred_title":"Data Scientist","salary_offered":"65 - 70 CAD \/HOUR","inferred_salary_from":65,"inferred_salary_to":70,"inferred_salary_yearly_from":135200,"inferred_salary_yearly_average":140400,"inferred_salary_yearly_to":145600,"inferred_salary_yearly_range_spread":0.08,"inferred_salary_currency":"CAD","inferred_salary_time_unit":"hourly","inferred_max_experience":8,"inferred_average_experience":6.5,"inferred_min_experience":5,"inferred_seniority_level":"Mid Level","sign_on_bonus":null,"url":"https:\/\/ca.linkedin.com\/jobs\/view\/data-scientist-at-agilus-work-solutions-4403083677","type":"Contract","category":null,"board":"Linkedin","post_date":"2026-04-19","is_remote":false,"html_description":"
Must Have Skills:<\/strong><\/p>
5- 8 years of experience with Python for data analysis, modeling, and scripting.<\/li>
5-8 years of experience with SQL for data manipulation and querying.<\/li>
2-5 years of experience in data preprocessing techniques, including data cleaning, transformation, and vectorization.<\/li>
2-5 years of experience in data mining, data profiling, modeling, cleansing, and enriching as well as extracting, transforming, loading (ETL) solutions.<\/li>
2-5 of experience in data privacy and security standards, especially when handling sensitive customer data within generative AI applications.<\/li><\/ul>
<\/p>
Nice-To-Have Skills:<\/strong><\/p>
Demonstrable experience or a strong theoretical understanding of Large Language Models (LLMs), including fine-tuning, prompt engineering, and an awareness of their current capabilities and limitations.<\/li>
Familiarity with or understanding of Retrieval Augmented Generation (RAG) architectures and their implementation for grounded, factual AI responses<\/li>
Familiarity with Agentic AI frameworks (e.g., LangChain agents, AutoGen) or designing multi-step AI reasoning processes<\/li>
Familiarity with Google Cloud Platform (GCP) or other cloud computing environments.<\/li><\/ul><\/body><\/html>","company":"Agilus Work Solutions","city":"Toronto","inferred_city":"Toronto","inferred_city_with_inferred_state":"Ontario | Toronto","inferred_cbsa":null,"fips":null,"is_metropolitan":null,"state":"ON","inferred_state":"Ontario","country":"Canada","inferred_country":"Canada","squirrel_codes":[]},"sort":[1776556800000]},{"_index":"job__1736258560_877903","_type":"_doc","_id":"205892250","_score":null,"_source":{"created":"2026-04-24T08:08:29.348395+00:00","unique_id":"7b57d4a6-1b8c-57cd-b85e-4f4d84fd10c3","key":"e9df198d9fbf2a0f238245c20da0a73e","title":"Data Scientist II","inferred_title":"Data scientist","salary_offered":"110000 - 140000 CAD \/YEAR","inferred_salary_from":110000,"inferred_salary_to":140000,"inferred_salary_yearly_from":110000,"inferred_salary_yearly_average":125000,"inferred_salary_yearly_to":140000,"inferred_salary_yearly_range_spread":0.27,"inferred_salary_currency":"CAD","inferred_salary_time_unit":"yearly","inferred_max_experience":7,"inferred_average_experience":5.5,"inferred_min_experience":4,"inferred_seniority_level":"Mid Level","sign_on_bonus":null,"url":"https:\/\/www.careerjet.ca\/jobad\/ca0ab4d225aa0088fdd830d0458887d4f6","type":"Full Time","category":null,"board":"careerjet","post_date":"2026-04-19","is_remote":false,"html_description":"Overview:<\/strong> Cotiviti is a leading solutions and analytics company that leverages financial datasets to deliver deep insight into the performance of retail system. These insights uncover new opportunities for retail organizations to collaborate to improve their financial performance and accuracy along with reducing inefficiencies. Cotiviti is seeking a handson Data Scientist to build productionready machine learning solutions that power the next generation of Retail Technology. Youll work with large on premise and cloud datasets, apply AI\/ML to real-world identification and validation challenges, and collaborate directly with auditors and engineers to deliver highimpact results. This role is perfect for an ambitious technologist who wants to ship real modelsnot conduct researchand make a direct impact in a fastmoving environment. This role aligns with our Retail Recovery Audit solution. . This role can be located within the US or Canada (Ontario area only) Responsibilities:<\/strong>

Work with key stakeholders both within R&D and Operations, along with product management to assess the potential value and risks associated with business problems that have the potential to be solved using machine learning and AI techniques.<\/li>
Develop an exploratory data analysis approach to verify the initial hypothesis associated with potential AI\/ML use cases.<\/li>
Document your approach, thinking and results in standard approaches to allow other data scientists to collaborate with you on this work.<\/li>
Prepare your final trained model and develop a validation test set for QA.<\/li>
Work with production operations to deploy your model into production and support them in monitoring model performance.<\/li>
Participate in other data science teams collaborating with your peers to support their projects.<\/li>
Participate in knowledge sharing sessions to bring new insights and technologies to the team.<\/li>
Participate in design sessions to continuously develop and improve the Cotiviti machine learning platform.<\/li>
Provide End to End value-based solutions, including data pipeline, model creation and application for end user consumption.<\/li>
Complete all responsibilities as outlined in the annual performance review and\/or goal setting.<\/li>
Complete all special projects and other duties as assigned.<\/li>
Must be able to perform duties with or without reasonable accommodation.<\/li> <\/ul> This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required. This job description does not constitute an employment agreement and is subject to change as the needs of Cotiviti and requirements of the job change. Qualifications:

MS or PhD. Degree in relevant discipline (Math, Statistics, Computer Science, Engineering or Health Sciences) or commensurate professional work experience.<\/li>
4-7 years experience in advanced analytics.<\/li>
3+ years experience in working in Big Data environments.<\/li>
Significant experience with SQL, ability to write SQL queries to efficiently extract data from relational databases.<\/li>
Experience developing machine learning models in an exploratory data analytics environment and working with others to develop production ready versions of the models that are deployed within operational environments.<\/li>
Experience in using machine learning tools to develop production strength models including, but not limited to, Python, TensorFlow, pandas, numpy, scikit-learn, spark, scala, hive, impala.<\/li>
Applied Machine Learning: Application of a variety of machine learning techniques to increase identification of payment integrity issues for our clients, reduce the cost of auditing processes or increase the quality of care and outcomes. Must have implemented machine learning solutions within production environments at scale.<\/li>
Big Data Analysis: Strong ability to manage and analyze data in a Big Data environment using a variety of scripts, potentially including but not limited to Scala\/Spark and Python as well as Cloud based ML\/AI capabilities.<\/li> <\/ul> Mental Requirements:<\/strong>

Critical Thinking: Ability to think critically and evaluate information objectively, considering different perspectives and potential implications before drawing conclusions or making recommendations.<\/li>
Attention to Detail: must have a keen eye for detail to ensure accuracy in data analysis, interpretation, and reporting.<\/li>
Quantitative Aptitude: Strong numerical skills are essential for conducting quantitative analysis, working with statistical methods and models, and manipulating data using mathematical operations.<\/li>
Data Interpretation: skilled in interpreting data visualizations, charts, graphs, and other forms of data presentation to extract meaningful insights and communicate findings effectively.<\/li>
Communication Skills: Effective communication skills are crucial for conveying complex technical concepts and insights to non-technical stakeholders clearly and understandably through written reports, presentations, and verbal discussions.<\/li>
Curiosity and Learning Agility: A strong desire to learn and explore new methodologies, techniques, and tools in the field of data analysis and insights generation is essential for staying current with industry trends and best practices.<\/li>
Resilience: The ability to handle pressure, adapt to changing priorities, and overcome setbacks is important in a fast-paced and sometimes ambiguous analytical environment.<\/li>
Ethical and Integrity: Upholding ethical standards and maintaining integrity in handling sensitive data and information is paramount for building trust and credibility in the insights provided<\/li> <\/ul> Physical Requirements and Working Conditions:<\/strong>

Remaining in a stationary position, often standing or sitting for prolonged periods.<\/li>
Repeating motions that may include the wrists, hands, and\/or fingers.<\/li>
Must be able to provide a dedicated, secure work area.<\/li>
be able to provide high-speed internet access \/ connectivity and office setup and maintenance.<\/li>
No adverse environmental conditions expected.<\/li> <\/ul> Base compensation ranges from $110,000 to $140,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our This role is based remotely and all interviews will be conducted virtually. Date of posting: 03\/16\/2026 Applications are assessed on a rolling basis. We anticipate that the application window will close on 06\/15\/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected. #LI-REMOTE #LI-RA1<\/body><\/html>","company":"Cotiviti","city":null,"inferred_city":"Ontario","inferred_city_with_inferred_state":"Ontario | Ontario","inferred_cbsa":null,"fips":null,"is_metropolitan":null,"state":"ON","inferred_state":"Ontario","country":"Canada","inferred_country":"Canada","squirrel_codes":[]},"sort":[1776556800000]},{"_index":"job__1736258560_877903","_type":"_doc","_id":"205986976","_score":null,"_source":{"created":"2026-04-24T08:47:22.069490+00:00","unique_id":"a6c4e37f-6991-5592-8b1b-f249f42d14f6","key":"1f02d720307b08063926cef4bffc633a","title":"Senior Data Scientist, Menu Personalization","inferred_title":"Senior data scientist","salary_offered":"140000 - 170000 CAD \/YEAR","inferred_salary_from":140000,"inferred_salary_to":170000,"inferred_salary_yearly_from":140000,"inferred_salary_yearly_average":155000,"inferred_salary_yearly_to":170000,"inferred_salary_yearly_range_spread":0.21,"inferred_salary_currency":"CAD","inferred_salary_time_unit":"yearly","inferred_max_experience":null,"inferred_average_experience":null,"inferred_min_experience":null,"inferred_seniority_level":"Entry Level","sign_on_bonus":null,"url":"https:\/\/www.careerjet.ca\/jobad\/ca3c486e7118c142999c6997341b3f8fe5","type":"Full Time","category":null,"board":"careerjet","post_date":"2026-04-19","is_remote":false,"html_description":"The role<\/strong> Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you! You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh's global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production. To succeed in this role you should be curious, able to deal with uncertainty, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally. What you'll do<\/strong>

Join and become an integral part of a high-impact team covering menu personalization.<\/li>
Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.<\/li>
Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.<\/li>
Design and execute A\/B tests to measure the impact of new recommendation strategies on key metrics.<\/li>
Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.<\/li>
Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.<\/li>
Analyze the performance of our models to understand customer behavior, and come up with improvements.<\/li>
Contribute to a collaborative and knowledge-sharing environment.<\/li> <\/ul> What you'll bring<\/strong>

Proven track record of scientific work in your Bachelor's, Master's, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.<\/li>
Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.<\/li>
In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.<\/li>
Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).<\/li>
Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.<\/li>
Experience with software development practices and tools (Git, CI\/CD, Docker, AWS).<\/li>
You love to learn, are a critical thinker and creative problem solver who strives for excellence.<\/li>
You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.<\/li>
Exceptional communication and collaboration capabilities.<\/li>
Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.<\/li> <\/ul> Interacting with product managers, UX designers, data and backend engineers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders. Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills, and we love diverse experiences! So even if you don't tick all the boxes but think you'd thrive in this role, we would really like to learn more about you. Let's cut to the cheese, this is why you'll love it here

Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.<\/li>
Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!<\/li>
Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance.<\/li>
Family Benefits - A parental leave top-up program for expectant parents.<\/li>
Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team<\/li>
Work Hard & Have Fun - From team socials to engaging company days, you'll have plenty of opportunity to experience the fun!<\/li>
Diversity & Inclusion Initiatives - With impactful ERG's like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.<\/li>
Food Puns - this one is kind of a big dill if you haven't already noticed. We even have some punny meeting room names!<\/li> <\/ul> Flexible Hybrid Approach At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week. #LI-HYBRID HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team. This is a posting for an existing vacancy. We are actively seeking to fill this position. #DATA Toronto, ON Pay Range $140,000 - $170,000 CAD<\/body><\/html>","company":"HelloFresh View all jobs","city":"Toronto","inferred_city":"Toronto","inferred_city_with_inferred_state":"Ontario | Toronto","inferred_cbsa":null,"fips":null,"is_metropolitan":null,"state":"ON","inferred_state":"Ontario","country":"Canada","inferred_country":"Canada","squirrel_codes":[]},"sort":[1776556800000]}]-->

Job Title	Company	Salary
Lead Data Scientist – Supply Chain	McKesson View all jobs	CAD 142,450
Founding Data Scientist	Book Depot	CAD 90,000
Senior Data Scientist	TechBlocks	CAD 124,800
Junior Data Scientist	Tech Consulting	CAD 67,600
Data Scientist	GSOBA	CAD 75,000
Lead Data Scientist – Supply Chain	McKesson	CAD 142,450
Data Scientist	Altis Technology	CAD 135,200
Data Scientist	Agilus Work Solutions	CAD 140,400
Data Scientist II	Cotiviti	CAD 125,000
Senior Data Scientist, Menu Personalization	HelloFresh View all jobs	CAD 155,000

Data Scientists Salaries in Ontario

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