KnowDis - Lead - Data Scientist - PhD

About the Role :

- At KnowDis you will move the world forward. Every day, we create innovative machine-learning solutions helping our clients across e-commerce, healthcare, and finance domains to solve their problems.

- We are a group of highly curious professionals who are dedicated to discovering and implement new Deep Learning Models. We work at the intersection of machine learning, statistical analysis, deep learning, natural language processing, and computer vision.

- We bring out the best in each other. And together, we work towards the vision of using this expertise to help society and make the world a better place.

- As a lead data scientist, you should be passionate about natural language processing, computer vision, statistical sampling and analytical methods, deploying machine learning models @ scale in production, monitoring and tuning them via active feedback loops. You will be part of an agile unit and will be collaborating with engineers, data engineers, and fellow data scientists.

- Your typical time distribution will be 70-80% on coding yourself, while 20-30% would go in managing, reviewing, and setting direction for a team of talented engineers.

Job Responsibilities :

1) Understand and analyze requirements requiring Machine Learning models from Product Owners, Customers, and other Stakeholders.

2) Be the end to end architect of new Machine Learning models.

3) Design innovative solutions by choosing the right algorithms, features, and hyperparameters.

4) Manage the full lifecycle of ML Models: Data Acquisition, Feature Engineering, Model 5) 5) Development, Training, Verification, Optimization, Deployment, Versioning.

5) Mentor fast-growing team of data scientists

Requirements for the Job :

1) Bachelor- s/Master's/PhD in Computer Science, Mathematics, Statistics or equivalent field and must have a minimum of 7 years of overall experience

2) Minimum 4-5 Years of experience working as a Data Scientist in deploying ML at scale in production

3) Experience in various machine learning techniques (e.g. NLP, Computer Vision, BERT, LSTM etc..) and frameworks (e.g. TensorFlow, PyTorch, Scikit-learn, etc.)

5) Proficient in deployment of Python systems (using Flask, Tensorflow Serving)

6) Previous experience in following areas will be preferred:

- Natural Language Processing(NLP) - Using LSTM and BERT; chatbots or dialogue systems, machine translation, comprehension of text, text summarization.

- Computer Vision - Deep Neural Networks/CNNs for object detection and image classification, transfer learning pipeline and object detection/instance segmentation (Mask R-CNN, Yolo, SSD).