Opportunity

Senior Data scientist with NLP and recommendation system experience, Twill by Maersk

In Twill, we’re on a mission to create a world where products and services can flow freely for everyone! We’re working to crack the code to digital logistics by taking away complexities and levelling the playing field for entrepreneurs, so nothing stands in their way when it comes to international trade.

Fast and accurate insights and automated decision making are integral to realizing this vision, and data science plays a key role in removing operational complexities and creating an easy and intuitive user experience that allows non-experts to navigate international logistics.

Our end vision is to create a platform that is so intuitive that self-service is the preferred option by customers, removing the need to raise cases with customer service. Instead, we will anticipate customer problems and handle them proactively and automatically on-platform through personalized interventions and recommendations. Data science is a key capability in this, where it will contribute with recognition of customer intent and recommendation of solutions. Furthermore, as we progress towards this vision, we will also be looking into intelligent automations of our case management to enable our customer care agents to better solve customer issues.

You’ll work alongside a team of curious and self-starting technical creatives interested in solving real-world problems. We plan as idealists and execute as pragmatists, we have a bias for action, we believe that innovation is our differentiator, and we celebrate our successes together.

No prior knowledge of logistics needed; we will help you learn what you’ll need to succeed.

The role

As a senior data scientist for issue resolution, you will work in a cross-functional product team where you will leverage statistical modeling, machine learning and large-scale distributed processing to contribute to building scalable solutions to address customer issues arising when interacting with our platform twill.net.

The products you will be building will be of two kinds: reactive solutions which will use intelligent automations of our existing case management solutions to give superpowers to our customer care agents, and on-platform customer-facing proactive solutions which will anticipate customer issues and resolve them before they materialize. The cross-functional team will consist of data science, data engineering, software engineering and product, and you will be empowered to take ownership of your domain, identify the solutions, and deliver them.

You should have demonstrated ability to make sense out of large, integrated datasets, and build statistical and machine learning models on top of these data sets. Hands-on experience developing NLP-based solutions (e.g., intent recognition from text) and recommendation systems is crucial for this role. You should also have experience in collaborating with software engineering and data engineering to put these models into production following best practices.

We are primarily looking for a strong technical profile with an inquisitive mind who is keen to contribute to our mission; a pragmatic team player that gets involved wherever the team needs and who can be our expert on all things NLP and recommender systems in the issue resolution and customer care domains. While prior experience working in these domains would be preferred it is not a hard requirement, there will also be subject matter experts in the team.

We’re about to start the execution our ambitious agenda for issue resolution, and you will have the opportunity to significantly shape this key focus area. As you help get this off the ground you should also expect some bumps along the way: we need to discover how to best reach the goal together. To support this, our culture encourages everyone to contribute wherever they can, which naturally leads to roles which are broader or T-shaped in nature. Therefore, in addition to working with data, you should also be comfortable working on a team with a shared mission for which data is only one of several parts, be comfortable engaging with different stakeholders like customer care, product and engineering and be excited to contribute to defining the future for tech-based issue resolution.

Key responsibilities & requirements

• You will play a key role in the issue resolution team, focusing on developing analyses and data products based on NLP and recommendation technologies
• Your primary responsibility is to develop, test and deploy data science solutions together with the team. In addition to the topics mentioned above, this can range from building integrated data sets over analyses to dashboards and machine learning models
• Hands-on experience building data products based on natural language processing (NLP) and recommendation technologies
• We expect you to be able to lead model development end-to-end incl. MLOps (problem formulation, modeling approach, implementation, testing and monitoring). You’ll probably have at least a couple of years of hands-on experience with this. We expect you to be able to work with our tool stack (Python, SQL, Spark, databricks, incl knowledge of common python data science libraries)
• Experience with a common dashboarding technology (we use PowerBI)
• Experience with collaborative development workflow: version control (we use github), code reviews, DevOps (incl automated testing), CI/CD
• Team player, eager to collaborate

Nice to haves

• Experience with issue resolution mitigation solutions, customer experience automations or case management automations
• Experience working in cross-functional product engineering teams following agile development methodologies (scrum/Kanban/…)
• Experience with Spark or other distributed compute paradigms
• Hands-on experience with mlflow, Kubernetes, Docker
• Research experience

As a performance-oriented company, we strive to always recruit the best person for the job – regardless of gender, age, nationality, sexual orientation or religious beliefs. We are proud of our diversity and see it as a genuine source of strength for building high-performing teams.