Data Scientist
Responsibilities
- Develop and evaluate statistical models for identification and classification of signs and events.
- Arrive at approximate bounds for accuracy of detection/classification/prediction given the finite dataset. Characterize the limitations of the dataset.
- Develop ML/statistical methods to aggregate data and arrive at more accurate predictions/detections (for example, minimizing effect of noise in the data).
- Identify errors or shortcomings in algorithms/ML techniques and propose methods to improve upon them.
- Develop validation framework even in cases where ground truth data may be either not very reliable or absent entirely.
- Good documentation of approaches.
Requirements
- Undergrad, masters or doctorate in a quantitative field.
- Experience working with, and reasonable understanding of the machine learning algorithms and methodology.
- Good hands-on experience of coding – Python (required), R, etc.
- Reasonable grasp of statistics and probability.
- Flexible and can-do approach. Ability to adjust to changing priorities.
Desired Skills
- Strong grasp of ML fundamentals, statistics and probability.
- Experience working with time-series, rare-event detection and data from GPS/IMU sensors would be useful.
- Experience with design of experiments.
To apply for this job please visit www.netradyne.com.
