Position: Data Scientist to help with audio tagging
Company: Bennett Data Science
Experience required: 2y
English level: intermediate

**Overview**:
We have an immediate need for a data scientist to help us characterize audio samples using deep learning.

The main objective is to **use a collection of labeled audio samples to build an accurate model that will assign the correct label to a hold-out set**.

The samples are clean and well-labeled, so no data cleansing should be necessary. This is strictly a modeling position for now.

You will work alongside a veteran team of data scientists. This could turn into a long-term project for the right candidate.

**Responsibilities (using Python)**:
- Work with our team to understand the project objectives and requirements
- Create a training, testing and hold-out set using the data provided
- Create spectrograms of each audio sample and extract salient features
- Use features to build a label (tag) predictor
- Report on the accuracy
- Additional work may focus on audio fingerprinting to identify duplicate samples

Prior experience with spectrograms is nice to have but not necessary.

**Requirements**:
- You must be a self-starter
- You must understand CNNs and how to use them for object detection
- You must understand how to explain model accuracy
- Bonus if you are a music lover