GTM Analytics Lead owning revenue data models, metrics, and Sales BI. Powering decisions for ButterflyMX’s smartphone - based building access platform.
About the role
- Senior Data Scientist at Plusgrade leveraging machine learning for dynamic pricing and offer allocation. Collaborating with cross-functional teams to enhance data-driven decision-making across diverse environments.
Responsibilities
- 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
- 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
- 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
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