Senior Data Scientist (Reinforcement Learning)

Senior Data Scientist

Plusgrade is fuel-led by fast-growing and complex data sources across multiple products, partners, and loyalty members, and right now our data science team needs someone who wants to own real-time continuous pricing models end-to-end, not just score them.

What You'll Be Doing

You will manage the data science needs for a portfolio of crucial global partners, taking complete ownership of your modeling solutions from initial research through to production deployment. A significant portion of your time will be focused on designing, testing, and optimizing advanced machine learning methodologies for real-time offer allocation, dynamic pricing, and deep personalization strategies. Working tightly with cross-functional product and engineering teams, you will establish global standards and best practices for real-time solutions across our travel ecosystem. AI workflows help re-engineer how software gets built at Plusgrade so code production, testing, and delivery are meaningfully restructured around it, ensuring you spend your capacity on high-leverage outcomes.

The Stack

Python · SQL · AWS · SageMaker · TensorFlow · PyTorch · Scikit-learn

What You Bring

• You possess a deep technical record of designing and deploying predictive analytics, machine learning algorithms, and large-scale optimization systems that solve complex, revenue-impacting business challenges.

• You are an expert in real-time decision-making systems or dynamic optimization problems, showing clear commercial acumen by aligning data science solutions directly with partner economics and business constraints.

• You move incredibly fast from idea to outcome, managing multiple competing priorities in a collaborative setting without needing hand-holding, and taking full technical accountability for scalable solutions across diverse data environments.

• You can conceptualize highly complex mathematical models and clearly translate your technical findings to non-technical executive stakeholders and product leaders with complete clarity.

• When it comes to AI, you raise the bar for your team by setting standards, architecting shared AI-assisted internal tools, and building repeatable, production-grade workflows that help the organization move materially faster.

Why Plusgrade

Travel is about the moments that make a journey feel personal. At Plusgrade, we build the technology that makes those moments possible, from upgrade offers and loyalty experiences to revenue tools used by 575+ airline, hospitality, cruise, rail, and financial services partners worldwide.

The work is global, complex, and rewarding. You will solve meaningful problems, take ownership from idea to outcome, and work alongside people who are smart, curious, and committed to doing great work.

We also give our teams access to AI tools and the encouragement to use them thoughtfully, to move faster, explore ideas, and build better ways of working.

We trust our teams to do their best work. That means autonomy, flexibility, and room to grow.

Come help us shape the future of travel.

What You'll Love About Us

🏦 RRSP Matching · 🏥 Comprehensive Health Plans · 📅 Flexible Paid Time Off · ✈️ Travel Experience Perk · 🧘 Annual Wellness Perk · 🚆 Commuter Perk · 🌅 Tenure-Based Work From Anywhere Program · 🍼 Parental Leave Top Up · 🌍 Adventure Pass · 🎓 Learning Allowance

Our Process

We believe every candidate deserves a fair, transparent experience, so regardless of outcome, everyone gets feedback.

Our process: Recruiter call → Hiring Manager interview → Final interview.

Plusgrade is an equal-opportunity employer committed to accessible recruitment. We welcome applications from all qualified individuals regardless of gender identity or expression, race, ethnic origin, creed, place of origin, age, sex, marital status, physical or mental disability, sexual orientation, or any other category protected by law. Accommodation is available upon request. We may use AI-assisted tools to help screen and assess applicants for this role. This posting is for an existing vacancy.

The base salary range is tailored to the advertised location and determined by several factors, including candidate expertise and internal peer equity. Final placement is based on a candidate's specific skill set and experience relative to the role's requirements.