Company Description
We are looking for a Senior Data Scientist (m/f/d) to be part of the development of our Business Intelligence Application. Our BI APP circle is embedded in our new circle cluster “Customer & Shop Intelligence”, which is in charge of driving a personalized and inspirational shop experience.
Our BI-APP Team uses data from across the company and transforms it into logics & scores, used to provide the best personalized user shopping experience. You will develop the algorithms powering our recommendations.
What you will do
- 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 recommendation 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.
Who you are
- At least 5 years of experience in working as a Data Scientist.
- 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.
- 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.
- 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.
- Familiarity with CI/CD tools (e.g., GitLab CI/CD, Hashicorp Terraform).
- Experience with generative AI frameworks (e.g., LangChain).
- Understanding of recommendation systems in e-commerce and retail.
- 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.
What you will get on top
- 40% employee discount in our shop.
- Flexible working hours or paid overtime.
- Hybrid working.
- Internal referral program.
- €16.80 mobility subsidy.
- Support in Relocation and VISA process.
- International & diverse working environment.
- Company pension scheme.
- Sports courses: e.g. gym membership and internal sport teams.
- Laracast & Egghead Account.
- Mental health & wellbeing workshops.
- In-house parcel station.
- Exclusive discounts via “Corporate Benefits”.
- Participating in Employee Share Program.
- Language courses.
- Free choice of hardware (Mac or Windows).
- Weekly changing benefits.
- Bike-Leasing (Swapfiets).
- State-of-the-art Technologies.