Data Scientist
Singapore, Singapore, Singapore
Applications have closed
Portcast
Our solution improves your supply chain resilience and profitability by accurately predicting arrival times and monitoring valuable container shipments around-the-clock.Portcast, a Singapore-based AI-powered logistics startup, has been focused on building the next-gen logistics operating system to predict how cargo moves across the world and enable data-driven decisions since 2017. We continue to play a pivotal role in how goods move around the world. Backed by some of the major investors in the tech industry, we believe that the logistics industry is at the inflection point of large-scale digitization.
Portcast is a team of young tech and industry talent building a game-changing product for the logistics and shipping industry. Our mission is to transform international supply chains to be more resilient by helping logistics companies realize the full potential of their data.
About the role
We are looking for an exceptional Data Scientist who is excited about redefining how the worlds’ largest cargo airlines, shipping lines, forwarders and shippers run global operations.
Your initial focus would be on our demand forecasting product which is a data heavy platform with an emphasis on enterprise time series forecast. The analytics engine that we’ve built helps logistics asset owners improve their capacity utilization, optimise their price and return on investments. We forecast 100k+ time series on a weekly basis that consists of more than 25 million predictions. Our forecasts answer questions like the following:
- What is the most profitable way of allocating a 20,000 TEU container ship?
- What would pre-holiday demand surge look like during Chinese New Year next year?
- What is the expected impact on utilisation if you increase the price by 10%?
What you will do
- Work collaboratively with data science, engineering, and business teams to improve and enhance data science solutions and processes.
- Deal with complex datasets.
- Analyze the data we have and drive the feature engineering efforts.
- Uncover the intricate patterns hidden underneath large data sets to derive actionable insights.
- Continue the development effort of our existing models and pipelines to create a scalable product.
- Create new prototypes of time series forecasting models based on latest research results, improve iteratively as needed to generate actionable insights and predictions.
- Work with the team to continuously identify the best external data sources that help improve the existing models.
- Present the work, results to the team and the clients regularly in a visual and easy to understand manner.
- Grow immensely professionally in a short period of time.
Requirements
Your skills & experience:
- A minimum of 3+ years of data science experience.
- Bachelor's or Master's Degree in Computer Science, Engineering or related disciplines.
- Has hands-on experience and skilled in Python, SQL.
- Has proven previous MLOps experience.
- Has experience in deploying, maintaining machine learning models previously in production environment with familiarity in config management, versioning etc.
- Genuine curiosity with the latest research in the field. Should be able to apply the same to solve the problem at hand.
- Experience in causal inference and forecasting is a plus.
- Demonstrated experience in two or more of the following: Supervised learning, Unsupervised learning, Statistical Analysis, Interpretable machine learning.
Join us now and help us make a dent in the supply chain industry!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Causal inference Computer Science Engineering Feature engineering Machine Learning ML models MLOps Pipelines Python Research SQL
Perks/benefits: Career development Startup environment
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