- This project requires a data scientist to build a python-based classification model prototype that analyses raw data files and establishes output data ranges across dimensions.
- This data model will deliver analytical results indicating type based on the inputted data.
- This model should run on all new samples received in our cloud, accepting payloads and outputting staged-output scores. Outputs will be appended to existing record for review, analysis, and reporting.
- Sample data is currently in an AWS cloud which is where your model will reside and be deployed. Upon completion, the deployed model will automatically ingest, process new data samples received through a web app and stored in an AWS DB, outputting classification results. Results will classify/stratify into groups of cohorts.
- Build, develop, and deliver core model in AWS infrastructure (EC2 (preferred), Sagemaker, Lambda, etc)
- Configure necessary AWS infrastructure to support the model
- Model must be deployed in AWS environment
- Model must process payloads and produce scores saved for reporting and access
- Daily or every-other-day check-ins to discuss updates, progress, challenges, and results
- 3-5 years of work experience.
- Good understanding of how machine learning, deep learning and A.I. algorithms work
- A person experienced in performing data analysis and model development for data set related to spectroscopy / chemo-metrics or similar will be an added advantage
- Extensive experience in model serving and workflow tools to enable rapid and reliable ML experimentation at scale.
- Practical cloud computing experience with AWS technologies utilizing infrastructure as code methodologies to create high performance and data intensive platforms.
- Programming skills in Python, R, SQL programming with the ability to quickly create prototype and debug solutions on Cloud Native / Linux /embedded platforms.
More information will be provided to the successful applicant.
Job Type: Contract
Pay: ₹400,000.00 - ₹500,000.00 per year
- Software Development: 2 years (Preferred)
- Scientific Research & Development
- Temporarily due to COVID-19