RNN Analysis of Global Cardiovascular Trends
Budget: €250 – €750 EUR
As a healthcare analytics assistant, I'm looking for a skilled data scientist to predict future trends in global cardiovascular disease rates utilizing a Recurrent Neural Networks (RNN) model. This will involve processing complex CSV data, which will include parameters such as patient age ranges, geographical regions, social conditions, and specific types of cardiovascular diseases.
Key responsibilities:
- Process distributed data using Hadoop/MapReduce or Apache Spark
- Developing an RNN model (preferably Python)
- Analyzing the complex CSV data (5000+ records)
- Identifying and predicting future trends based on age, region, types of diseases and other factors
- Properly visualizing results in digestible diagrams
Ideal candidates should have:
- Experience in data analysis with Python
- Solid understanding of Hadoop/MapReduce or Apache Spark
- Proven ability in working with Recurrent Neural Networks
- Excellent visualization skills to represent complex data in static or dynamic dashboards
- Experience working on virtual machines with Ubuntu
All candidates will need to complete a short exercise to demonstrate a min requirements for this task.
Key responsibilities:
- Process distributed data using Hadoop/MapReduce or Apache Spark
- Developing an RNN model (preferably Python)
- Analyzing the complex CSV data (5000+ records)
- Identifying and predicting future trends based on age, region, types of diseases and other factors
- Properly visualizing results in digestible diagrams
Ideal candidates should have:
- Experience in data analysis with Python
- Solid understanding of Hadoop/MapReduce or Apache Spark
- Proven ability in working with Recurrent Neural Networks
- Excellent visualization skills to represent complex data in static or dynamic dashboards
- Experience working on virtual machines with Ubuntu
All candidates will need to complete a short exercise to demonstrate a min requirements for this task.