ABOUT PLUSGRADE
Travel is not just about the destination; it's about every memory made along the way. We are dedicated to shaping the future of travel by partnering with 250+ airline, hospitality, cruise, passenger rail, and financial services companies to create new, meaningful revenue streams through incredible customer experiences. Rooted in our core values of being ambitious, innovative, and collaborative, we are driven to continuously raise the bar, exceed expectations, and bring out the best in everyone, fostering a culture where we believe we are better together, working towards an extraordinary future in travel. Come help us transform everyday travel into extraordinary experiences.
ABOUT THE ROLE:
Plusgrade, fueled by fast-growing and complex data sources across multiple products, partners, and loyalty members, is creating a world of cutting-edge analytics that operates in real time, is automated, is always active, and is continually evolving. This collective intelligence is our unique offering, empowering us to drive unmatched member engagement and optimize program economics for our partners.
The Senior Data Scientist, reporting to the Senior Manager, Data Science, will play a key role in supporting Plusgrade's Data Strategy, a cornerstone of our organizational growth. As the Senior Data Scientist, they will not only manage data science needs for a portfolio of important partners but also research, develop, and deploy top-tier modeling solutions across our entire partner ecosystem. They will harness data science methodologies to solve complex business challenges. They will provide guidance and collaborate with fellow data scientists to help achieve the goals of various business areas.
WHAT YOU WILL BE DOING:
Reporting to the Senior Manager, Data Science, you will:
- Building Reinforcement Learning models to solve business problems in a production environment.
- Drive significant incremental business value by leveraging advanced machine learning to design, test, and implement advanced data science approaches for dynamic pricing, real-time offer allocation, and personalization, improving targeting and offer assignment within our marketing engine.
- Develop and optimize algorithms that balance business constraints, customer behavior, and engagement objectives to deliver optimal, data-driven decisions across offers and pricing.
- Design, enhance, and generalize models into scalable solutions that can be applied across products, partners, and diverse data environments.
- Leverage a wide range of data sources (e.g., partner, product, and third-party data) to enrich algorithms and clearly demonstrate measurable business impact.
- Lead and collaborate with cross-functional teams (Product, Engineering, Analytics) to establish best practices for developing, automating, and standardizing advanced data science solutions, with an emphasis on real-time applications.
- Champion scalable, automated production deployments by integrating algorithms into live systems through rapid iteration and experimentation, leveraging AWS infrastructure (particularly SageMaker) to deploy, monitor, and scale models in production.
YOU ARE SOMEONE WITH:
- Extensive experience shipping Reinforcement Learning models
- 4+ years of experience researching, designing, and developing machine learning algorithms, with a strong focus on solving real-world business problems.
- Expertise in developing algorithms for real-time decision-making or dynamic optimization problems, such as offer allocation, continuous pricing, or recommender systems.
- Proficiency in machine learning, large-scale data processing, predictive analytics, and optimization techniques.
- Strong programming skills in Python, with hands-on experience using machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Advanced SQL skills and familiarity with relational databases, enabling efficient manipulation of large and complex datasets.
- Hands-on experience working in AWS environments, particularly with SageMaker for building, training, deploying, and monitoring machine learning models at scale.
- The ability to conceptualize, design, and communicate complex algorithms to technical and non-technical stakeholders clearly and concisely.
- Innate curiosity to solve complex problems, derive actionable insights and iterate on innovative solutions
- Strong business acumen and an ability to align data science initiatives with commercial goals, ensuring measurable business impact.
- A quantitative Master's or Ph.D. is required, or equivalent experience. Relevant fields include, but are not limited to, Computer Science, Engineering, Mathematics, Statistics, and Operations Research.
WHAT YOUβLL LOVE ABOUT US:
π¦ RRSP/401(k) Matching
π₯ Comprehensive Health Plans
π
Flexible Paid Time Off
βοΈ Travel Experience Credit
π§ Annual Wellness Credit
π₯ Team Events
π» Commuter Credit
π
Work From Anywhere Program
πΌ Parental Leave Top Up
π Adventure Pass
OUR PROCESS:
Plusgrade is an equal-opportunity employer and is committed to providing an accessible recruitment process. We welcome applications from all qualified individuals and are committed to equal employment opportunities regardless of gender identity or expression, race, ethnic origin, creed, place of origin, age, sex, marital status, physical or mental disability, sexual orientation, and any other category protected by law. Upon request we will provide accommodation for applicants with disabilities. If you have a preference regarding the language of your interviews, please inform our Talent Team when they reach out to you.
We believe in diversity and inclusivity and that is why our interview process is designed for a positive candidate experience and to ensure every candidate is evaluated equally. We may utilize technology-assisted/ artificial intelligence tools to help us screen, assess, and select applicants for this position. This job posting is for an existing vacancy.
All applications will be reviewed from our Talent Team and the successful candidate(s) will go through the following recruitment process:
All candidates will be provided with feedback regardless if they pass or didnβt pass any of our interview stages. All your information will be kept confidential.
