Data Scientist
2 months ago
Signal Ocean is the technology arm of the Signal Group, a leading provider of innovative solutions for the shipping industry. Our primary product, The Signal Ocean Platform, enables shipping professionals to securely handle, integrate, and assess intricate collections of private and public shipping data. Driven by advanced machine learning and artificial intelligence, our technology suite provides tailored, exclusive insights that support our clients in achieving performance and efficiency.
The team: The hiring team oversees the data, models, and relevant backend infrastructure responsible for modeling the global shipping market, monitoring movements, and commodity trades. The role is integral to this process, centered on the development of production-ready online NLP models designed to understand and interpret vital information within a variety of shipping reports.
About the RoleIn this role, you will be working closely with the data science team to deliver cutting-edge ML/AI products and solutions to Signal's clients. If you are interested in working at the intersection of artificial intelligence/machine learning, software engineering, and advanced business analytics, and if you have the skills and drive to create and improve novel algorithms, models, and technology products that professionals love, then we would love to hear from you.
At Signal, we are committed to finding people who are respectful, inclusive, and team players, embodying these values in every role.
Key Responsibilities- Utilize Python to create robust, object-oriented software capable of high-performance computing using both high- and low-level language features.
- Develop and design engineering solutions to meet the constraints of the data science algorithms.
- Build solutions that allow the analysis of large amounts of information from the company databases to discover trends and patterns, drive optimizations and improvement of product development and business strategies.
- Develop processes and tools to monitor and analyze model performance and algorithm accuracy.
- Collaborate with data science and product development teams.
- Communicate engineering needs and findings in a clear and concise way, both verbally and in writing.
- Stay curious and enthusiastic about using algorithms and state-of-the-art research to solve problems.
- Implement and maintain CI/CD processes.
- Extensive experience in Python with strong knowledge of architectural patterns and object-oriented design and implementation.
- 5+ years of post-academic developer experience.
- Experience with LINUX.
- Strong skills working with algorithms, computational complexity.
- Good understanding of computational complexity.
- Able to design, build, and maintain efficient and reliable code.
- Familiarity in working with data visualization tools.
- Experience in working with data wrangling on large datasets (SQL/NoSQL).
- Passionate and talented in quickly assimilating technology and science ideas.
- Problem-solving aptitude, analytical mind, and business acumen.
- Comfortable in acting as a point of contact; explaining complicated methods and data to non-technical colleagues/clients.
- Good organization skills and willingness to work in and help the team.
- Excellent command of written and spoken English (company's working language).
- Experience with cloud platforms, ideally including Azure.
- Experience with Kubernetes.
- Generous compensation with additional performance incentives.
- Coverage under the company's collective health insurance plan.
- Opportunity to work alongside experienced people with deep knowledge in software engineering, data science & shipping business who are always eager to mentor.
- Signal's hybrid remote work policy currently includes 6 working days at premises per month, during which happy hour events take place.
- 2-4 weeks of onboarding training to prepare you for your new role, having the opportunity to meet about 30 trainers while diving deep into our products and/or the shipping world.
- Career growth opportunities and a structured development discussion every 4 months.
- Personal learning budget for training, seminars, conferences (750 to 2000 EUR annually depending on seniority).
- Regular team bonding events and activities.
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