Oliver Wyman - Sr. Lead Data Scientist or Principal Data Scientist at Stryker Corporation — NeverHard
Oliver Wyman - Sr. Lead Data Scientist or Principal Data Scientist at Stryker Corporation in Toronto, Ontario. Skills: Collaboration, Data Engineering, Infrastructure Deployment, Leadership, Machine Learning. Apply on NeverHard.
Company
Stryker Corporation
Location
Toronto, Ontario
Type
part_time
Remote: Yes
Required skills:
Collaboration
Data Engineering
Infrastructure Deployment
Leadership
Machine Learning
Project Management
Risk Management
data science
strategy
Boston, Chicago, New York, Dallas, Toronto, Montreal
Lead Data Scientist
Who We Are
OliverWyman is a global leader in management consulting. With offices in over 50 cities across 30 countries, we combine deep industry knowledge with expertise in strategy, finance, operations, technology, risk management and organizational transformation. Our 4,000+ professionals help clients optimize their business, improve IT, operations, and risk profiles, and accelerate performance to seize attractive opportunities. We deliver innovative, customized solutions to CEOs and executive teams of the top Global 1000 companies.
Practice Overview
At OliverWymanDigital we partner with clients to deliver breakthrough outcomes for their toughest digital challenges. We blend digital technology with industry expertise to tackle disruption, create impact, modernize technology, harness value from data and analytics, and build resilience for tomorrow’s risks. We work collaboratively with clients’ leaders, employees, stakeholders and customers to jointly define, design, and achieve lasting results.
Role and Responsibilities
Our clients drive our projects, and no two OW Digital projects are the same. As Lead Data Scientist you will primarily manage technical projects, including data engineering, model selection/design, and infrastructure deployment in both internal and client environments. You should be comfortable developing methods and selecting approaches based on first principles thinking, curiosity, and a strong foundation in software engineering, while delivering solutions that meet business needs.
Explore data, build models, and evaluate solution performance to resolve core business problems
Explain, refine, and collaborate with stakeholders through the model‑building journey
Stay current on domain state‑of‑the‑art techniques and emerging modeling and data‑engineering methodologies
Advocate best practices in modeling, code hygiene, and data engineering
Lead the development of proprietary statistical techniques, algorithms, or analytical tools on projects and asset development
Work with Partners and Principals to shape proposals that leverage our data science and engineering capabilities
Your Experience & Qualifications
Technical background in computer science, data science, machine learning, artificial intelligence, statistics, or related quantitative science
Compelling track record of designing and deploying large‑scale technical solutions, delivering tangible, ongoing value:
Built and deployed robust, complex production systems implementing modern data science methods at scale, including supervised and unsupervised learning
Leveraged cloud‑based infrastructure‑as‑code (e.g., CloudFormation, Bicep, Terraform) to enable rapid, repeatable deployment across environments
Demonstrated poise in time‑boxed environments, making rapid design decisions
Fluency in modern programming languages for data science (≥Python), covering the full ML lifecycle (data storage, feature engineering, model persistence, inference, observability) using open‑source libraries
Knowledge of one or more machine‑learning frameworks (Scikit‑Learn, TensorFlow, PyTorch, MxNet, ONNX, etc.)
Familiarity with modern storage and computational frameworks, with cloud‑first considerations for Azure and AWS
History of side projects or open‑source contributions is valued but not required
Solid theoretical grounding in the mathematical core of data science
Deep understanding of modeling or analytical techniques (Bayesian modeling, time‑series forecasting, etc.)
Fluency in statistics, linear algebra, and vector calculus
Experience presenting at high‑impact data science conferences and active connections to the data science community are highly valued
Interest or background in financial services, capital markets, healthcare, life sciences, consumer, retail, energy, or transportation industries
Your Attributes
Undergraduate or advanced degree from a top academic program
Passion for technology and solving problems
Pragmatic approach to solutioning and delivery
Excellent communication skills, both verbal and written
Commitment to creating impactful solutions that solve client problems
Ability to work fluidly and respectfully with a talented team
Willingness to travel for client and internal stakeholder meetings
Our Values & Culture
Rewarding work
– Reputation for high quality work and collaboration with major brands on exciting projects, supported by a culture of recognition.
Progressive employment
– Flat structure, strong I&D values, and advancement based on merit, with health benefits, a 401(k) match, and continuous improvement.
Enjoyable days
– Commitment to career development, mentoring, and opportunities for social impact during company time.
Balanced lives
– Support for flexible hours and work-from-home options to achieve work‑life balance.
We offer a competitive total rewards package which includes health and welfare benefits, tuition assistance, 401(k) savings, and employee assistance programs.
Salary and Benefits
The applicability base salary range for this role is $150,000 to $195,000. Base pay will be determined based on experience, skills, location, certifications, and education, and any applicable minimum wage requirements. The position may also be eligible for performance‑based incentives.
Equal Opportunity Employer
OliverWyman is an equal opportunity employer. Our commitment to diversity is genuine, deep, and growing. We are not perfect, but we are working hard to make our teams balanced, representative and diverse.
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