As a Data Scientist in ZeroNorth you will help bring value to the customer by building data-driven products & solutions. We are specifically looking for someone with an interest in building and deploying LLM-based solutions to optimize operational processes in the shipping industry.
Key responsibilities:
Ideate, develop, deploy and test data science and machine learning solutions within and about our products and operations.
Explore and analyse our data universe consisting of billions of data points, for example on fuel consumption, commercial planning, voyage planning and weather data.
Use large bodies of human-generated text in combination with open-source LLMs to improve operational efficiency.
Build production-ready APIs in collaboration with the data engineering team.
Create and optimise advanced analytics algorithms, likely using methods from fields such as machine learning, operations research, mathematical optimisation, or Bayesian modelling.
Collaborate with your team to ensure your developments make an impact, for example with Data Engineers to hook into data pipelines, with Software Engineers to deploy into live products and with Product Managers and actual users to ensure business viability.
Your profile:
3+ years of experience, working on innovative data science solutions, ideally with demonstrated business impact.
Strong knowledge and practical experience in one or more relevant fields, such as machine learning, mathematical optimisation, operations research, causal inference, Bayesian modelling, differentiable programming.
Experience working with collaborative software engineering practices (Git, Agile, DevOps), and methodologies for systematic and continuous analytics delivery (DataOps, MLOps).
Strong expertise in SQL and Python for data processing and analytics.
Excellent communication skills to share your findings and approaches with a wide range of audiences, from technical peers to business stakeholders.
A pragmatic, conscious mindset when trading off development speed versus building fundamentals.
Relevant educational background in computer science, mathematics, engineering, physics or similar.