65 Data Science jobs in Toronto

**Our Purpose**
_Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential._
**Title and Summary**
Vice President, Data Science
Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.
Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. Do you have a passion for developing products using leading-edge technology that solve for key industry pain points?
Role:
The Vice President will provide strategic leadership and direction, overseeing key business functions to drive growth and innovation. This role involves managing a team of data scientists and analysts in cross-functional teams, ensuring operational excellence, and fostering a culture of collaboration and continuous improvement. The Vice President will develop and implement strategic initiatives, align departmental goals with the organisation's vision, and maintain strong relationships with stakeholders. The ideal candidate will possess exceptional leadership skills, a deep understanding of the industry, and the ability to translate strategic objectives into actionable plans.
You will also lead a team of highly skilled data science analysts in data quality initiatives and tasks in a multi-product environment. You will drive excellence in execution, automation and identify new and novel ways to enhance the overall data quality of our products and business process.
You've been involved in defining AI strategies and aligning those strategies to data, product and business strategies to support and enhance the overall success of those strategies. You will contribute to the overall data strategy for the organization and assist with the strategy to align our data and processes with the AI strategy and lead the incorporation of AI for revenue generation, process optimization and data quality.
All About You:
- Proven ability to develop and execute data science strategies that align with business goals and objectives.
- Deep understanding of data science principles, algorithms, and techniques including supervised and unsupervised learning, deep learning, natural language processing and have extensive knowledge of the low-level details behind these algorithms.
- Recent experience leading GenAI initiatives focused on leveraging the latest capabilities of ChatGPT, Gemini or similar.
- Several years of prior experience as a senior level data scientist developing and deploying machine learning and deep learning solutions end-to-end (data exploration to deployment).
- Skilled in recruiting, mentoring, and managing high-performing teams.
- Passionate about leveraging advanced analytics and machine learning to drive innovation.
- Strong track record of partnering with senior leadership and cross-functional teams.
- Exceptional ability to convey complex technical information to diverse audiences.
- Focused on defining OKR's, KPIs and metrics to measure the impact and effectiveness of product workflows and data science projects.
- Ability to translate data insights into strategic business recommendations.
- Ensures adherence to data governance policies and standards.
- Ability to explain complex algorithms and results to variety of audiences
Experience working:
- Previously as a data scientist with experience in Python, R Programming, ML Frameworks (Scikit learn) and Deep Learning Frameworks (TensorFlow, PyTorch)
- Preferably in the AzureML suite of machine learning technologies or prior experience with either AWS or Google machine learning tools and technologies.
- With the following technologies SQL, SAP HANA, Hadoop, Snowflake, Linux, Azure, Azure Machine Learning, Databricks, Apache Spark (PySpark/Scala)
- With analysts to build reporting and dashboards for business use cases
- With data analysis, statistical analysis and the ability to convey complex analysis to broad audiences
- In a cloud based big data environment and deploying machine learning models at scale
- With source control, production and non-production environments and automated build and deployment
- Ideally you have experience in banking, e-commerce, credit cards or payment processing and exposure to both SaaS and premises-based architectures.
Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.
**Corporate Security Responsibility**
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
+ Abide by Mastercard's security policies and practices;
+ Ensure the confidentiality and integrity of the information being accessed;
+ Report any suspected information security violation or breach, and
+ Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
The Driver team aims to provide a best in class driving and earnings experience that enables anyone to join the platform and make a living. As a Data Scientist on the Driver Experience & Segments team, you will collaborate with our world class team of engineers, product managers, and designers to design the end-to-end driving experience for hundreds of thousands of drivers who interact deeply with our app every day. You will be a key partner in creating innovative ways to reward and recognize our best drivers, building tools to provide guidance to drivers on how to maximize their earnings, and designing the best UI and personalized XP to match the right rides to the right drivers quickly. This Scientist's role will inform the driver experience for all drivers, in particular our most valuable ones, and help to improve their take home earnings.
Data Science is at the heart of Lyft's products and decision-making. You will leverage data and rigorous, analytical thinking to shape our Driver products and make business decisions that put drivers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features.
**Responsibilities:**
+ Leverage data to provide insights around driver behavior and sentiment and identify improvement opportunities
+ Apply analytics, inference and experimentation techniques to solve business problems
+ Design and analyze experiments; communicate results to technical and non-technical audiences to act on launch decisions
+ Establish metrics that measure the health of our driver products and driver experience
+ Develop analytical frameworks and dashboards to monitor business and product performance
+ Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
+ Design and implement data pipelines to support data analysis and product implementation
**Experience:**
+ Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
+ 4+ years experience in a data science role or analytics role
+ Proficiency in SQL - able to write structured and efficient queries on large data sets
+ Experience in programming, especially with data science and visualization libraries in Python or R
+ Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
+ Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners
+ Experience in applying machine learning techniques a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
+ Experience working with ETL pipelines a plus
**Benefits:**
+ Extended health and dental coverage options, along with life insurance and disability benefits
+ Mental health benefits
+ Family building benefits
+ Child care and pet benefits
+ Access to a Lyft funded Health Care Savings Account
+ RRSP plan to help save for your future
+ In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
+ Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
+ Subsidized commuter benefits
Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Application Deadline:

11/09/2025

Address:

33 Dundas Street West

Job Family Group:

Data Analytics & Reporting

This role will require 3-5 days in the Toronto office

Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modeling data. Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.

• Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.
• Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.
• Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
• Uses analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
• Develops prediction systems and machine learning algorithms. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
• Collaborate together with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.
• Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
• Provides specialized consulting, analytical and technical support.
• Exercises judgment to identify, diagnose, and solve problems within given rules.
• Works independently and regularly handles non-routine situations.
• Broader work or accountabilities may be assigned as needed.

Qualifications:

Intermediate level of proficiency:

• Mathematics, statistics & operations research.
• Deep learning.
• Machine learning.
• Trust, bias and ethics.
• Creative thinking.
• Critical thinking.

Advanced level of proficiency:

• Big data.
• Data visualization.
• Computational thinking and programming.
• Data wrangling.
• Data preprocessing.
• Creative reasoning.
• Verbal & written communication skills.
• Collaboration & team skills.
• Analytical and problem solving skills.
• Influence skills.
• Data driven decision making.
• Advanced Python programming skills and extensive experience in predictive modeling is mandatory for this role. Some experience in SAS and AWS sage maker will be an asset.
• Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
• Deep knowledge and technical proficiency gained through extensive education and business experience.

Salary :

$82,800.00 - $154,800.00

Pay Type:

Salaried

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: 

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at .

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
Lyft's Data Science Team builds mathematical models underpinning the platform's core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment.
We are hiring for a variety of Data Science interns, focusing on the following specialties:
**Optimization:** Construct and fit statistical or optimization models that facilitate automated decision making in the app.
**Machine Learning:** Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment.
**Inference:** Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems.
You will report into a Science Manager.
**Responsibilities:**
+ Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context
+ Perform exploratory data analysis to gain a deeper understanding of the problem
+ Write production modeling code; collaborate with software engineers to implement algorithms in production
+ Design and run both simulated and live traffic experiments
+ Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions
**Experience:**
+ **Currently pursuing a Masters or PhD degree at a university in Canada (required)** in mathematical sciences ( **Operations Research, Computer Science, Statistics** , Applied Mathematics, Theoretical Physics, Behavioral Science, Electrical Engineering, etc.), Economics (Microeconomics Theory, Econometrics etc.), Data Engineering; or a related field; AND with **a graduation date between December 2026 and June 2027 (required)**
+ Available during **Summer 2026** for an internship in Toronto
+ Experience coding in **Python (required)** or SQL, R; standard data science libraries (NumPy, Scikit-learn, PyTorch, TensorFlow, Keras); and ML Tools & Libraries (NumPy, SpaCy, NLTK, Scikit-learn, TensorFlow, Keras)
+ Experimental design and analysis
+ Exploratory data analysis
+ Expertise in one of these specialties: optimization and mathematical modeling, machine learning fundamentals, or probabilistic and statistical modeling
+ Bonus points: Experience in marketplace design, ridesharing, studying two-sided marketplaces, and/or transportation
**Benefits:**
+ Mental health benefits
+ In addition to holidays, interns receive 2 days paid time off and 3 days sick time off
+ Subsidized commuter benefits
_Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request._
_Lyft highly values having employees working in-office to foster a collaborative work environment and company culture._ _This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays._ _Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers._ _#Hybrid_
_The expected base pay range for this position in the Toronto area is $45-$48/hour CAD. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process._

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
The Rider organization is responsible for the Lyft Rider App, spanning the full consumer journey from request and purchase to pickup, in-trip experience, drop-off, and time between rides. Within this org, the Rider Offerings team owns growth and service excellence across Lyft's portfolio of offerings - ensuring each ride option is reliable, intuitive, and high-quality. The team also plays a critical role in Lyft's global expansion and shaping the future of AV/PV hybrid rideshare experience.
This role will deliver the data science foundations that shape how riders choose and experience Lyft's offerings. The right candidate will apply experimentation, measurement, and modeling to guide product decisions that drive adoption, service reliability, and long-term user retention. They will shape the future of Lyft's core rideshare offerings in partnership with product, design, engineering, and marketing stakeholders throughout the organization.
**Responsibilities:**
+ Design and analyze experiments to optimize service excellence across offerings - measuring reliability, growth, and rider retention.
+ Build models and reporting frameworks that explain rider choice, conversion, and retention across different ride modes and product offerings.
+ Establish metrics that measure the health of Lyft rideshare offerings and rider experience. Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and actions
+ Develop insights that inform product strategies and global market adaptation.
+ Contribute to Lyft's experimentation and observability frameworks to ensure scientific rigor and actionable results.
**Experience:**
+ Bachelor's or Master's degree in a quantitative discipline (Computer Science, Statistics, Economics, Mathematics, Operations Research, or related field).
+ 2-4 years of experience in applied data science, analytics, or related roles.
+ Strong proficiency in SQL and Python (or R), with experience analyzing large-scale datasets.
+ Solid foundation in experimentation design, causal inference, and applied statistics.
+ Demonstrated ability to translate complex, ambiguous problems into clear analysis and recommendations.
+ Effective communication skills to influence product and cross-functional partners.
**Benefits:**
+ Extended health and dental coverage options, along with life insurance and disability benefits
+ Mental health benefits
+ Family building benefits
+ Child care and pet benefits
+ Access to a Lyft funded Health Care Savings Account
+ RRSP plan to help save for your future
+ In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
+ Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
+ Subsidized commuter benefits
Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
Data is at the heart of how Lyft makes business and product decisions. As a data science team, we work collaboratively with partners across product, engineering, operations and growth to develop business insights and make actionable recommendations. We're looking for passionate data scientists to take on some of the most interesting and impactful problems in ridesharing.
You'll work in an environment where we embrace moving quickly to build the world's best transportation. Data Scientists pursue a variety of problems ranging from understanding our passengers and drivers, to ensuring we have an efficient marketplace, to optimizing how we run our marketing and growth incentives. You'll dig into the data to uncover insights, design experiments and measure the impact, and help influence decision-making across the entire organization.
As a **Data Science Intern on the Decisions: Product track** , you will focus on Data Science for humans. Your output shapes decisions made by executives, product managers, operations and business teams, and beyond. This role relies upon an ability to apply decision frameworks and a deep understanding of the business and product to drive alignment on problems and solutions.
You will report into a Science Manager.
**Responsibilities:**
+ Build and automate relevant models and reporting for important business processes
+ Perform deep-dives into our customer data to understand passenger and driver behavior
+ Develop strong hypotheses, create solutions, and uncover business insights to increase growth
+ Design and analyze experiments to increase engagement with the Lyft platform
+ Partner and develop strong relationships with diverse teams across product, marketing, and engineering
**Experience:**
+ Pursuing a Bachelor's or Master's degree in data science, computer science, economics, applied math, engineering, statistics or another quantitative field; or in a hard science field, such as physics, biology, biostatistics, etc.
+ **Currently attending a university in Canada (required) AND graduating between December 2026 and Summer 2027 (required).** **For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience.**
+ Available during **Summer 2026** for the internship in Toronto
+ Experience in and comfortable working with very large datasets
+ Experience analyzing data in Python or R; **strong proficiency in SQL**
+ Experimentation design and analysis of A/B tests
+ Effective communication skills; detail-oriented
+ Passion for community, sustainability, or transportation
+ Ability to thrive in a fast-paced environment
**Benefits:**
+ Mental health benefits
+ In addition to holidays, interns receive 2 days paid time off and 3 days sick time off
+ Subsidized commuter benefits
_Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request._
_Lyft highly values having employees working in-office to foster a collaborative work environment and company culture._ _This role will be in-office on a hybrid schedule - Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays._ _Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers._ _#Hybrid_
_The expected base pay range for this position in the Toronto area is $42-46/hour CAD. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process._

**Position Snapshot**
**Business areas: Nestlé Canada**
**Job title: Specialist Product Ownership - Data Science (1-year contract)**
**Location:** **North York, ON located at 25 Sheppard Ave W, North York, ON M2N 6S8;**
**Hybrid**
**A little bit about us**
While Nestlé is known for KitKat, Gerber, Nescafe, and Häagen-Dazs, our recipe for success comes down to one thing: our people.
We strive to lead a people-focused culture that empowers employees to bring their authentic selves to work each day. There are 3,000+ members of Nestlé Canada celebrated for taking action using agility, courage, and trust to find solutions that benefit the business or greater good. We're a team of changemakers, who are curious and challenge the status quo, that take risks that will help drive us forward.
Our focus is not only on nourishing our customers, but also about enriching you. We know that empowerment leads to strong employee engagement, a great work culture, and motivated employees.
**Position Summary**
We are seeking a professional to leverage AI and decision science to develop mathematical solutions that address business needs, enhance value, and facilitate process transformation. This role involves managing the delivery of these solutions and translating business challenges into analytical insights using forecasting, machine learning, generative AI, optimization, simulation, and various AI methodologies.
**A day in the life of a** **Specialist Product Ownership** - **Data Science** **:**
**AI Service Delivery & Business Impact:**
+ Delivery of AI-driven mathematical solutions that enhance business value and streamline processes
+ Prompt and efficient response to business challenges using AI methodologies that lead to process improvements and increased efficiency
**Stakeholder Management & People Transformation:**
+ Communication of AI findings and recommendations with businesses and functional SMEs in non-technical language
+ Facilitate change management through engagement with stakeholders to foster understanding and adoption of AI-driven processes
**People Management:**
+ Foster a culture of innovation and continuous learning among the team of data engineers and AI specialists
+ Drive the upskilling of team members in AI methodologies
**Role Requirements**
+ **Master's degree in applied Statistics** , Mathematics, Computer Science, AI, or a related field
+ Minimum 3 years working with BIG or complex data sets in a statistical/analytical/AI role
+ Proficient in AI & data visualization techniques (e.g., Python, Spark, R, MS Power BI, and open source)
+ Proven experience in developing algorithms and predictive models using AI methodologies
+ Experience with Generative AI and OpenAI technologies
+ Experience in development lifecycle of solution and migration and testing strategies
+ Knowledge of agile, scrum, hackathon, and design thinking methodologies
**Desirable skills:**
+ Experience in R programming, Python, and Information Modelling/ETL within SQL
+ Business knowledge in "FMCG/CPG" OR "Retail" industry
**Benefits**
+ Flexible and hybrid work arrangements
+ Excellent training and development programs as well as opportunities to grow within the company
+ Access to the Discount Company store with Nestlé, Nespresso, and Purina products (Located across various Nestle offices/sites)
+ Additional discounts on a variety of products and services offered by our preferred vendors and partnerships
**What you need to know**
We will be considering applicants as they apply, so please don't delay in submitting your application.
Nestlé Canada is an equal-opportunity employer committed to diversity, equity, inclusion, and accessibility. We welcome qualified applicants to bring their diverse and unique experiences as a result of their education, perspectives, culture, ethnicity, race, sex, gender identity and expression, nation of origin, age, languages spoken, veteran's status, colour, religion, disability, sexual orientation and beliefs.
If you are selected to participate in the recruitment process, please inform Human Resources of any accommodations you may require. Nestlé will work with you in an effort to ensure that you are able to fully participate in the process.