Senior Data Scientist
Paris, France
Applications have closed
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"Wir sind Ihr digitaler Logistikpartner im LKW-Güterverkehr für Komplettladungen. Als führender europäischer Spediteur bieten wir Zugang zu tausenden LKWs. Unsere Technologie bringt Transparenz und Flexibilität in die Branche, spart Kosten,...- Apply data science concepts to solve problems like pricing optimization, load-to-carrier recommendation, load search and logistics network optimization, among others;
- Define the new state-of-the-art for machine learning engineering in the road logistics services;
- Develop machine learning expertise beyond basic supervised and unsupervised learning, mentor and be mentored by other team members;
- Prototype and subsequently operationalize innovative, data-intensive, end-to-end machine-learning-based decision engines, following the latest best practices on MLOps;
- Enforce the best principles in ML System Design by balancing the feedback loop on data exploitation and data acquisition, follow the 80/20 ruling, focus on the right metric in every design decision and once a shippable amount of value is created, go live, evaluate, learn and iterate;
- Demonstrate your leadership skills and manage a Machine Learning based project or product, which you will define through frequent cross-functional interactions with your peers as well with experienced logistics professionals and Technical Product Owners, among other stakeholders;
- Highly motivated with excellent communication and strong interpersonal skills;
- M.Sc or PhD in a quantitative field and/or working experience as a Data Scientist or Machine Learning Engineer;
- T-shaped mindset: actual expertise on a single area but the ownership/willingness to contribute to the product end to end in order to ensure a healthy value creation chain;
- Teamaholic. We don’t believe in super-heroes but rather in super-teams: teams that own products and are the single unit of work :)
- Proficiency in Python with ability to translate ideas into prototypes and prototypes into production;
- Experience with working on Machine Learning projects to learn from structured data as well as deep knowledge on statistics;
- Fluent written and verbal communication in English;
- Deep knowledge of the theory and expertise on the application of Machine Learning;
- PhD in Machine Learning and/or data mining fundamental topics and/or non-trivial applications of ML/DM foundations;
- Top tier academic track on ML related conferences (e.g.: KDD, NeurIPS, ICML, AAAI, ECML/PKDD);
- Solid Python and software engineering skills, including best practices like CI/CD and Git;
- Proven experience in contributing to machine learning engineering teams in industry (2+ yrs.);
- Experience on MLOps in modern cloud systems (preferrably, AWS);
- Experience with Agile philosophies (e.g.: Scrum, Scrumban, Kanban, XP) and project management tools (e.g.: JIRA);
- A fast-growing scale-up, where your work will make an impact on our growth and lead to several career
opportunities; - An international team of 900+ people with 65+ nationalities spread across 11 offices in 7 countries with English as our company language;
- Culture of trust, constructive feedback and self-organization with a forever-agile mindset;
- A quarterly feedback and review process for personal development;
- A structured promotion process, providing everyone with fair and transparent career growth;
- Learning and development opportunities on the job and through conversations with your manager;
- Various opportunities to connect with colleagues, formally and informally, digitally or in person (when
allowed), through regular team events, company get-togethers, and partnership events with other companies
and local organizers.; - When in office: unlimited snacks, drinks, and fruits;
- Compliance with COVID-19 restrictions when required with remote interviews, onboarding, and working;
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile AWS CI/CD Data Mining Engineering Git ICML Jira Kanban Machine Learning MLOps NeurIPS PhD Python Scrum Statistics
Perks/benefits: Career development Conferences Team events Unlimited paid time off
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