We are looking for a data scientist (logistics) to tackle some of South-East Asia's most complex logistical challenges. Think of systems that can schedule millions of orders per day for delivery, estimate lead and arrival times of customer orders, indicate where items should be placed in our warehouses for efficient utilisation of time and space, do path planning for our pickers in warehouses that pick tens of thousands of items per day, etc. Together, with a team of talented individuals, you will work to conceptualise, develop and productionalise intelligent systems aimed at increasing the efficiency of our logistics. The work is done closely with the business where we consult and work out the implementation to improve relevant business metrics.
You will work in a vertically integrated team of engineers, analysts, data scientists and product managers. You are expected to formulate clear problem definitions, work on proof of concepts to demonstrate the feasibility of new projects and also help carry this into production. Sound fundamentals on basic data science concepts as regression, classification and clustering problems is to be expected. Knowledge and experience in applying operations research techniques is highly preferred. We’re looking for a candidate who is proactive, challenges the status quo and has a strong drive to improve some of the region’s most difficult logistical problems.Job Requirements
- Over 5 years relevant working experience, operations research in the supply chain/logistics area will be an advantage
- Solid programming skills in at least one language (preferably Python)
- Good working knowledge of SQL
- Experience in data analysis and machine learning libraries (pandas, numpy, seaborn, ggplot, sk-learn, TensorFlow etc.)
- Given that we do optimization problems in Java, candidates must have an inclination towards taking up Java in day to day activities
- Knowledge of networking problems
- Knowledge of JVM languages (Scala, Kotlin, Java)
- Experience in applying operations research techniques in academic or business context
- Knowledge of operations research libraries (CPLEX, Gurobi, Optaplanner, etc.)
- As you will be working in the logistics domain any domain expertise in transport, warehousing or aviation is highly valued
- Hands on experience with data visualisation tools such as Tableau, Spotfire, Qlik, etc.
- Exposure to cloud platforms such as AWS, Azure, etc.