Applied Science Manager

Role Overview:

At McAfee, we’re on a mission to leverage cutting-edge machine learning techniques to deliver personalized experiences, optimize pricing strategies, and make a tangible impact on our customers’ lives. Join our Consumer ML team and help shape the future of AI-driven solutions in a collaborative, growth-oriented environment.
As the Manager of Machine Learning Science, you will lead a team of ML scientists dedicated to applying advanced ML principles to build algorithms and models that drive dynamic pricing and personalized recommendations. You will work hands-on with your team to ensure the design, implementation, and deployment of impactful AI & ML models aligned with McAfee's business goals.
In this hands-on leadership role, you will manage and mentor the ML Science team and collaborate closely with the ML Engineering and ML Data Engineering teams to develop scalable and robust ML solutions. Your leadership will be pivotal in blending innovation with practical implementation, ensuring that the models you create are optimized for performance and business impact. Additionally, you will contribute to McAfee’s broader AI and ML strategy, reporting directly to the Senior Manager of Consumer Machine Learning and ensuring that the team’s work aligns with strategic objectives while fostering a culture of growth and continuous learning.
This is a position based in Canada. We will only consider candidates in Canada and are not offering relocation assistance at this time.

About the Role:

• Leadership & Team Development: Lead and mentor a high-performing team of ML scientists. Foster a collaborative culture that promotes innovation, continuous learning, and technical excellence.
• Strategic Vision: Drive the ML Science strategy for pricing, recommendation systems, and personalized consumer experiences, aligning efforts with McAfee’s objectives to optimize customer value.
• Model Development: Oversee the design, implementation, and delivery of ML models using user behaviour and subscription data to enhance personalization and product value. Familiarity to traditional and classical ML is a plus.
• Reinforcement Learning Implementation: Guide the team in applying reinforcement learning techniques, such as contextual bandits, SARSA, and Q-learning. Implement exploration-exploitation strategies like epsilon-greedy, Thompson sampling, and Upper Confidence Bound (UCB) to optimize decision-making frameworks for pricing and recommendation engines.
• Cross-Functional Collaboration: Work closely with teams across Marketing, Product, Sales, and Engineering to ensure that ML solutions align with strategic objectives and deliver measurable business impact.
• Optimization & Experimentation: Lead the team in creating algorithms for optimizing consumer journeys, increasing conversion rates, and driving monetization strategies. Design and execute controlled experiments (A/B and multivariate tests) to validate and improve model performance.
• Research & Knowledge Sharing: Stay at the forefront of ML science, contributing to the development of new algorithms and applications. Share knowledge through internal presentations, publications, and participation in academic or industry forums.
   

About You:

• 8+ years of experience in machine learning, with 3+ years in a leadership role managing ML scientists. You’ve demonstrated the ability to drive technical innovation and mentor teams.
• Proven track record in at least one of the following: Implementing AI/ML personalization techniques to enhance consumer/customer product experiences; Developing AI/ML-based dynamic pricing and personalized offer strategies for pricing optimization, or Creating customer/consumer churn and propensity models specifically for digital subscription use cases
• Expertise in classical ML and deep learning techniques (XGBoost, Random Forest, SVM, deep neural networks, etc.), reinforcement learning techniques (contextual bandits, SARSA, Q-learning), and proficiency in Python, SQL, and ML frameworks.
• You are proficient with ML libraries like PyTorch, Scikit-learn, and others. You have a strong background in feature engineering, model validation, and evaluation metrics.
• You possess a deep understanding of the mathematical and statistical principles behind machine learning algorithms (e.g., linear algebra, calculus, probability) and are driven by solving complex problems. You have a track record of researching and applying new ML techniques to solve real-world challenges.
• You are an effective communicator who can explain complex ML concepts to technical and non-technical stakeholders. You excel in collaborating with cross-functional teams to align ML models with business goals.

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Company Overview

McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users’ needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.

Company Benefits and Perks:

We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.

• Bonus Program
• Pension and Retirement Plans
• Medical, Dental and Vision Coverage
• Paid Time Off
• Paid Parental Leave
• Support for Community Involvement

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.