Data Scientist, Data & Analytics, Global IT
DSV
Lisbon, PT
há 4 dias

Job Req Number : 40102

40102

At DSV we are looking for a Data scientist with business understanding to be part of our Data & Analytics team in Global IT .

  • The focus of our team is to build advanced end-2-end solutions that create direct business value for DSV’s divisions, including for example : customs declaration automation;
  • vendor invoices automation; address validation; ETA prediction; and many more to come

    The word advanced is used to underline that 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.

    However, fancy technologies and accurate ML models do not solve the issues at hand alone; we strive to combine our competencies to build holistic solutions where the underlying complexity is hidden for the user to create simple and value-adding experiences.

    As a Data Scientist your main responsibilities and activities will be :

  • Meeting with stakeholders, discussing their needs and translating them into Data Science problems.
  • Conduct data-driven analyses to provide input to decisions (e.g. which DSV country to start with for a specific use case).
  • Identify proper solutions / models / pre-trained models for particular business cases.
  • Preprocess the data (cleaning, transforming) for ML models.
  • Train ML models on prepared training data using GPU on cloud and on premises.
  • Test and evaluate ML models and present conclusions on further improvements.
  • Use and tweak existing frameworks for running automated testing and evaluation of ML models.
  • Mature models to be available as services for other components.
  • Present your results on an ongoing basis to team mates and business stakeholders.
  • We expect you to have experience with most of the following technologies / areas :

  • Code languages : Python (using both OOP as well as popular libraries such as Pandas, Scikit),
  • Solid understanding of Machine Learning in practice : be able to speak about several projects you participated in,
  • Very good knowledge of Deep Learning with focus on NLP : Transformers, Bert family and where it all came from,
  • ML Frameworks : TensorFlow / PyTorch and other open-source frameworks,
  • ML model serving : TensorFlow serving, Torch serving,
  • Cloud : Azure,
  • Modern software development : good understanding of DevOps, CI / CD, MLOps,
  • Basic knowledge of database technologies such as :
  • Relational database : We use MySQL
  • NoSQL database : We use MongoDB
  • Version control : Git (we use Atlassian BitBucket as a GUI on top of Git)
  • It is a bonus if you also have some experience with some of the other technologies that our team works with, such as :

  • Code languages : Java, Scala
  • Authentication : Open ID Connect 2.0 (we use Red Hat KeyCloak as identity broker)
  • Containerization : Docker
  • Container orchestration : Kubernetes
  • CI / CD Pipelines : Jenkins (our templates are written in Groovy)
  • Load balancing : NGINX
  • Installation scripts : Ansible
  • Event streaming : Confluent Kafka, K streams
  • Requirements : Jira
  • Documentation : Confluence
  • Frontend technologies : React JS, Material UI, JavaScript / TypeScript, Redux
  • Test framework : Jest
  • You like to :

  • Learn new stuff from knowledgeable colleagues
  • Analyze problems using data and statistics
  • Present your results to teammates and business stakeholders to communicate your findings
  • Solve problems that are too complex for deterministic reasoning with the use of Machine Learning
  • Find pragmatic solutions that balance the need between what is the optimal solution from a theoretical standpoint with what is possible within the constraints set by project deadlines, low data quality, etc.
  • Understand the data and the business logic that is related to the ML models you test, train and improve, and you believe that this in-depth understanding is pivotal for being able to deliver valuable results
  • Take a lot of responsibility both for exciting R&D work to push the boundaries of ML, but also for doing the necessary nitty gritty work it takes to prepare data, evaluate results, debug errors, etc.
  • Ensure that your models can be tested iteratively to compare the individual model’s accuracy and the entire solution’s accuracy over time and to make this visible to stakeholders
  • Break down the solutions into iterations so they can deliver value quickly in MVP versions before they are enriched with more nice-to-have functionality in later iterations
  • Reach out to others for help or clarifications whenever you need it and to ensure alignment with others
  • Make realistic mockups of data to allow you to test things swiftly on synthetic data before you get access to production data
  • We are an ambitious team with a flat hierarchy and a mix of young and very experienced persons , who are working according to the following principles :

  • We celebrate victories together
  • We take responsibility for mistakes and learn from them
  • We design for scale but build only for the near future
  • We value working software and informal alignment over tedious documentation
  • We make decisions based on knowledge and insight rather than hierarchical structures
  • Decisions are the product of conversations between people with different competencies (not one person)
  • Everyone can speak their honest opinion
  • We have all the needed competencies to build awesome products inside the team : Product owner, Business analysts, Application developers (frontend + backend), Data engineers, Data scientists, ML engineers, DevOps engineers.

    Job / Environment

  • Your job location will be Portugal (Lisboa, Saldanha) and you will be part of DSV Global IT with peers working in remote teams across the Globe
  • International Environment
  • Permanent Contract with 35h / week
  • DSV Global Transport and Logistics

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