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Job Description
We are seeking an Applied Scientist to join a collaborative machine learning product team focused on delivering innovative solutions that enhance the customer experience. This role offers the opportunity to work on large-scale, real-world problems and contribute to impactful projects across key business areas.
Our team builds large-scale demand forecasting systems that power replenishment decisions for more than 100 buying teams. Online fashion is one of the most challenging forecasting contexts, with millions of data points (including clickstream signals) and demand patterns that shift rapidly under the influence of social media and trends.
We combine strong MLOps and software engineering practices with rigorous experimentation—regularly testing new forecasting techniques and benchmarking them against our production models. Today, we forecast both continuity lines and fast-moving trendy products shortly after they launch, ensuring our business can respond quickly and confidently to customer demand.
Key Responsibilities
* Collaborate within a cross-functional team to develop and deploy large-scale machine learning systems.
* Lead the implementation and scaling of algorithms with measurable business impact.
* Design and conduct experiments to validate models and inform product direction.
* Stay current with developments in the field through research, reading groups, and prototype testing.
* Contribute to ongoing improvements in code quality, infrastructure, and feature development.
* Participate in learning opportunities, knowledge-sharing sessions, and technical events.
* Promote diversity, equity, and inclusion in both team culture and work practices.
Qualifications
About You
* Demonstrated experience applying machine learning in production environments.
* Depending on the team's focus, relevant experience could include areas such as deep learning, forecasting, optimization, recommender systems, causal inference, or Bayesian methods.
* Proficiency in programming languages used in machine learning and familiarity with common frameworks.
* Solid grasp of statistical methods and software development best practices.
* Ability to work independently, manage timelines, and deliver prototypes or models aligned with business needs.
* Strong collaboration skills and comfort working across technical and non-technical roles.
* An interest in research and innovation, with any publications in reputable machine learning venues considered a plus.
Benefits
* Competitive compensation and performance-related bonuses
* Professional development and career growth support
* Generous paid leave, including additional personal celebration days
* Flexible benefits allowance
* Access to learning resources and internal knowledge-sharing events
* Employee perks and wellness support options
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