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Senior Data Scientist – Reinforcement Learning
PlusgradeSenior Data Scientist developing Reinforcement Learning models at Plusgrade for travel industry analytics and member engagement optimization. Collaborating with data scientists to enhance organization’s data strategy and business value.
Tech Stack
Tools & technologiesAWSPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- RRSP/401(k) Matching
- Comprehensive Health Plans
- Flexible Paid Time Off
- Travel Experience Credit
- Annual Wellness Credit
- Team Events
- Commuter Credit
- Work From Anywhere Program
- Parental Leave Top Up
- Adventure Pass
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Reinforcement Learningmachine learning algorithmsreal-time decision-makingdynamic optimizationpredictive analyticsoptimization techniquesPythonSQLTensorFlowPyTorch
Soft Skills
problem-solvingcommunicationcollaborationcuriositybusiness acumen
Certifications
Master's degreePh.D.