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Our client makes logistics profitable, with accurate cargo predictions. They use proprietary machine learning algorithms and real-time external market data (economic indices, marine weather and satellite-based data) to predict how much cargo will be shipped, from where and when will it arrive.
Data sourcing, engineering and pipeline management Time series data analytics using latest machine learning Spot patterns and trends in data and propose new models / refinements News crawling / sentiment analytics Programming in Python, using AWS, SciPy stack / Keras and latest software development systems In this role, you will be responsible for analyzing time series data as well as news crawling / sentiment analysis engine for live customer projects supporting some of the largest players in the logistics and maritime . The purpose of this analytics engine is to help logistics asset owners improve their capacity utilization and return on investments. You'll be required to be an end-to-end data scientist. The role includes understanding business needs, developing a proof-of-concept, data collection, and productionizing your data product
Curious & analytical Comfortable working with large amounts of data: facts, figures, and number crunching Strong understanding of machine learning models Able to compare different predictive models on different data sets and generate reports Smart and hardworking individual who can work under pressure within a tight deadline A team player As an early member of an ambitious startup, the growth opportunities will be aplenty
Please apply using the following link: https://snaphunt.com/jobs/76085821