Programmer needed to Convert "R" Random-Forest models into stand-alone Java or C/C++ Code

Project Description

We are a medical devices startup that is working on accurate, affordable screening for the early detection of heart disease. We need a Data Scientist who can convert models developed in R into generic Java or C/C++ code that can be executed on an Android Platform.  The conversion methodology and/or tools used are left to the contractor’s discretion, as long as the results can be validated to be correct.  

This position is for an intermediate or senior experienced level individual who is competent in software programming as well as state of the art machine learning practices – preferably in a Medical Device setting.

Here are some detailed required and desired skills:

Must-Have:

5+ years of experience in developing models using Machine Learning techniques such as:

• Random Forest (must have)
• Gradient Boosting
• Support-Vector-Machine (SVM)

5+ years of experience in Software Programming using one or more of the following languages:

• C
• C++
• Java
• Android Java

Experience with at least two or more of the following AI/Machine Learning platforms:

• R (must have)
• SAS Enterprise Miner
• Weka
• TensorFlow Lite
• Salford Systems

Also desired (but optional):

3+ years of experience in the Medical Device Industry (or working in a regulated environment)

Experience with or knowledge of ECG machines

Statistical Analysis skills and generating documentation with the following:

• p-values
• Sensitivity/Specificity
• AUC / ROC plots
• PPV/NPV

Experience in Design Validation for Medical Devices

Experience with Atlassian tools (Jira, Stash/Git, Bamboo, etc.)

Familiarity with Android Applications and Java coding

Ability to work on-site in our Lewisville, TX facility 

Proposal Requirement

Please specify experience in Machine learning techniques (random forest), software progreamming, AI/Machine learning paltforms and R expertise.

Previous work that you have done that is relevant.