Chief Data Scientist for AI/ML En­gi­ne­e­ring, Analytics & MLOps


Job Req Number: 57354 
Time Type: Full Time

Do you want to push the boundaries of machine learning and scale it to users across the world? Have you grown weary of empty buzzwords and proof of concepts which never materialize? Do you wish for a product centric work environment, where machine learning and analytics drive action – not just insight?

With a strong focus on the MLOps discipline you will take part in the innovation and design of new products, as well as tweak and mature existing ones. You will become the technical lead of a small team of highly talented data scientists and collaborate with several product teams consisting of product owners, backend- and frontend developers and DevSecOps specialists. You will be responsible for a product agnostic guild of ML engineers and data scientists, aiming to create and continuously enhance the ML framework of tomorrow.

Join a department focused on our most valuable digital products

You will join the Data & Analytics department. The purpose of our department is to build advanced end-to-end products which create direct business value for DSV’s divisions, including:

  • Customs declaration automation
  • Vendor invoices automation
  • Booking distribution
  • Address validation
  • ETA prediction

The use cases we solve tend to have a high degree of complexity, requiring non-deterministic problem solving (i.e., the use of ML/AI), near real-time data processing, a need for high availability, vertical and horizontal scalability, and a very high volume of transactions. We strive to build holistic solutions, where the underlying complexity is hidden from the user, resulting in simple and value-adding experiences.

Your new unit is divided into cross-functional product teams with a mix of young and highly experienced colleagues. We strive to base our work on knowledge and insight rather than hierarchical structures, and we make sure that our decisions are based on conversations between people with different competencies rather than one individual.

Be the driver of our AI/ML and analytics journey

As our coming Chief Data Scientist, you are best described as a playing coach. You can provide inspirational apprenticeship and mentorship to junior colleagues, and you will want to get your hands dirty with our MLOps platforms, as well as designing, implementing, and enhancing the following areas of our Machine Learning practices:

  • MLOps architecture: Architecting and building enterprise data and AI platforms while ensuring information security standards are always followed. Additionally, you will design state-of-the-art MLOps flows to ensure that the surrounding processes are robust, modular, scalable, deployable, reproducible, and versioned.
  • Data generation in the product: ML & Data Science is not a separate area, but an integrated part of the product team. Therefore, the data generated from our products is already aligned closely between those building the product and those training the models with this data. You will have a big say in how we tweak this data to ensure the data quality is extremely high to provide the needed feedback when the users correct predictions coming from our models.
  • Data gathering: You will also work with our automated pipelines for sharing the data from our products to our re-training pipelines in our ML Ops platform.
  • Re-training of models: Using the collected data, you will work with pipelines for automatic re-training of models
  • Model evaluation: You will work with automatic testing and evaluation of models against the current model in production to ensure that only models that perform more accurately will be put into production.
  • Deployment of models: If the model passes the evaluation thresholds, you will make sure the new model is deployed automatically and that the previous model is decommissioned.
  • Model monitoring & alerting: You will make sure that models are being monitored and that automatic alerts are in place so that no model drift is taking place for the models running in production.
  • Auto-healing: Based on ongoing evaluations, certain event can automatically trigger that the system is improving itself (e.g., determining which types of predictions need manual verification, and which types have high enough proven accuracy to be automatically verified)
  • Explainability: Work closely together with the product developers to ensure that product provides enough transparency to the users to ensure that they feel in control and understand why the system does what it does.
  • Data Science ways of working: you will challenge our current approaches and put forward long-term vision for the whole Data Science stream in Data & Analytics.
  • Guarding data science stream effectiveness: you will keep data science stream effectiveness as priority. You will challenge developments/changes in other D&A guilds which might deteriorate/impact DS ways of working.

You thrive when solving high-complexity challenges

Solving problems too complex for deterministic reasoning with the use of machine learning, you need to be able to thoroughly analyze problems using data and statistics. With these skills, you make realistic mockups of data to allow you to test things swiftly, finding pragmatic solutions that balance between the theoretical standpoint and what is possible.

Additionally, we expect you to have experience with most of the following technologies:

  • MLOps frameworks: Google Vertex AI & Kubeflow are the core of our MLOps platform. Furthermore, we expect that you have substantial experience with other MLOps (AWS, Azure, other) solutions and you can challenge our ways of working.
  • Cloud architecture: We use GCP and Azure
  • ML Frameworks: PyTorch & TensorFlow
  • ML model serving: TorchServe & TensorFlow Serving
  • Coding languages: Python & Java
  • Database technologies such as: MySQL & MongoDB
  • Version control: Git, DVC, Azure DevOps
  • Containerization and orchestration: Docker & Kubernetes

Want to know more and apply?

We will be happy to answer any questions you may have regarding the position and about your options in DSV. You are welcome to call Group Chief Data & Analytics Officer Peter Sergio Larsen, on +45 29 28 71 41.

We look forward to receiving your application via the link below as soon as possible. We will process the applications as we receive them.

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