Ocean Freight Exchange is the world-leading, AI-driven marketplace transforming the $1.3 trillion bulk shipping industry by optimizing ship chartering processes between ship owners, charterers and brokers. We are backed by the top venture capital firms including Corigin, NextView (the Co-Founder of Linkedin), Accomplice, and Foundation Capital (an early investor in both Uber and Netflix). We are the 1st place winner in the Singapore government's Pier71 technology competition 2018. Come see what it's like to take on extraordinary transformations every day, in an environment buzzing with smart people (including software architects and data scientists in areas of NLP and Deep Learning) who understand and respect what you do.
The Lead Data Scientist will work with our passionate software engineers and data scientists on expanding the personalization and Machine Learning capabilities of the AI platform. If you have a passion for Machine Learning and experience with personalization, recommendation systems, and a demonstrated history of delivering results, then we are very interested in speaking to you.
- Contribute to the research, design and construction of cutting-edge AI systems for large volumes of data processing that meet the needs of millions of vessel locations, terminals, ports, cargoes, and transactional data
- Apply emerging AI technologies (e.g., Deep Learning) to product and user data to take recommendation systems and contextual personalization to the next level, as well as to devise new data products
- Rapidly iterate and develop algorithmic/model-based approaches, based on Machine Learning techniques, to prediction/targeting problems
- Work closely with Engineering team to "productionize" winning approaches
- Master or PhD in Computer Science, Statistics, Electrical Engineering, Applied Mathematics, or a related field with 4+ years of experience
- Fluent in building/prototyping Machine Learning models, algorithms and wrangling large datasets
- Knowledgeable about standard personalization approaches (e.g., Matrix Factorization techniques, Neighborhood techniques)
- Hands-on experience in Deep Learning (e.g., CNN, RNN, LSTM), model selection techniques (e.g., K-fold Cross Validation), Word Embeddings (e.g., Fasttext, GloVe Word2Vec), Genetic Algorithms, Generative models, Supervised and Unsupervised Learning, Bayesian Statistics, Pathfinding, Natural Language Processing, Image Processing
- Proficient in using Python (e.g., Numpy, Scipy, Scikit-Learn, Tensorflow, Theano, Keras) and R to implement Machine Learning models and algorithms
- Demonstrated experience with actually shipping code, getting data science into production
- AWS/Google Cloud experience
- Some low level programming experience ( C/C++/Fortran/Java/Go, etc.)
- Experience with big data & emerging technologies (Spark/Flink/Vowpal)
- Strong research experience in ML, demonstrated by publications in top ML conferences (NIPS, ICML, ICLR, KDD, so on).
- Pair programming sessions with experienced engineers to exchange ideas and learn
- Work with a team of experienced and dedicated developers in the creation of our next innovation platform
- Challenge yourself with exciting projects in a fast-paced and constantly changing start-up environment.
- Exposure to exciting new platforms and high scalability technologies
- Make a difference as you watch your work change the lives of others