Senior Data Scientist - Search (all genders)

Design and develop innovative algorithms to power a personalized shopping experience, leveraging cutting-edge machine learning techniques
Deploy your solutions into production, taking full ownership and ensuring high performance and scalability
Combine your data science expertise with a pragmatic, agile approach to find innovative solutions and drive measurable results within a fast-paced environment
Challenge the status quo by identifying areas for improvement in existing retrieval and reranking systems, particularly those relying heavily on business logic, and propose data-driven solutions
Thrive in a dynamic, fast-paced environment with a flat hierarchy, where your ideas and contributions can make a real difference
Proficiency in Python or experience with at least one scientific computing language (e.g., MATLAB, R, Julia, C++)
Strong SQL skills with experience in analytical or transactional database environments
Theoretical understanding of machine learning principles, coupled with a hands-on approach to building and iterating on models
Proven experience in building and deploying machine learning solutions that deliver tangible business value
Strong understanding of data structures, algorithms, and tools for efficiently handling large datasets (e.g. pandas, numpy, dask, arrow, polars)
Experience designing, building, and managing data pipelines
Familiarity with cloud-based model training and serving platforms (e.g., GCP Vertex AI, Amazon SageMaker)
Solid understanding of statistical methods for model evaluation
Big Data: Experience analyzing large datasets using statistical and machine learning techniques
DevOps: Familiarity with CI/CD tools (e.g., GitLab CI/CD, Hashicorp Terraform) is a plus
Generative AI: Experience with generative AI and agentic frameworks (e.g., LangChain, ADK, CrewAI, Pydantic AI) is a plus
Understanding of recommendation, retrieval and reranking systems in e-commerce and retail is a plus
Excellent written and verbal communication skills in English
Ability to effectively communicate complex machine learning concepts to both technical and non-technical stakeholders
Proven ability to collaborate effectively within a team to establish standards and best practices for deploying machine learning models
A proactive approach to knowledge sharing and fostering a quick development environment
Nice To Have
Experience with BigQuery Knowledge of time series and (graph) neural network models
Familiarity with statistical testing and Gaussian Processes
Strong Knowledge of Computer Vision libraries, (e.g. OpenCV, TensorFlow, PyTorch)
Experience maintaining Machine Learning pipelines through MLOps frameworks (e.g. MLFlow, Kubeflow)
Experience with deep learning libraries (e.g., TensorFlow, PyTorch)
Experience building interactive dashboards (e.g. using Streamlit, Voila, Gradio)
Experience with GCP or AWS, including infrastructure-as-code and CI/CD pipelines
Practical knowledge of Docker

Employment type
Full-time

Work arrangement
Hybrid