Ninja Van is a late-stage logtech startup that is disrupting a massive industry with innovation and cutting edge technology. Launched 2014 in Singapore, we have grown rapidly to become one of Southeast Asia’s largest and fastest-growing express logistics companies. Since our inception, we’ve delivered to 100 million different customers across the region with added predictability, flexibility and convenience. Join us in our mission to connect shippers and shoppers across Southeast Asia to a world of new possibilities.
More about us:
– We process 250 million API requests and 3TB of data every day.
– We deliver more than 1.5 million parcels every day.
– 100% network coverage with 1000+ hubs and stations in 6 SEA markets (Singapore, Malaysia, Indonesia, Thailand, Vietnam and Philippines), reaching 500 million consumers.
– 600,000 active shippers in all e-commerce segments, from the largest marketplaces to the individual social commerce sellers.
– Raised US$400 million over four rounds.
We are looking for world-class talent to join our crack team of engineers, product managers and designers. We want people who are passionate about creating software that makes a difference to the world. We like people who are brimming with ideas and who take initiative rather than wait to be told what to do. We prize team-first mentality, personal responsibility and tenacity to solve hard problems and meet deadlines. As part of a small and lean team, you will have a very direct impact on the success of the company.
Roles and Responsibilities
Design, develop and maintain machine learning models to support business and operational processes.
Develop pipelines to train, validate and deploy these models to production systems.
Work closely with stakeholders to explore, develop and validate data science solutions for business initiatives.
Contribute to key product and engineering decisions, and lead the implementation of major data science initiatives.
Develop the firm’s data science capabilities – identify opportunities, share knowledge and drive adoption of data science solutions
Strong Computer science fundamentals, deep knowledge of supervised, unsupervised and reinforcement learning techniques, and excellent problem-solving skills.
At least 5 years of experience in a similar role, with a demonstrated track record of developing machine learning models at scale.
Advanced knowledge of data query and manipulation tools (e.g. Spark, PrestoSQL, Pandas), and machine learning frameworks and libraries (e.g. PyTorch, TensorFlow, XGBoost, scikit-learn).
Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics or related field from a top university.
Data storage: Percona XtraDB, Elasticsearch, Delta Lake
Data pipelines: Apache Kafka, Spark Streaming, Maxwell