Data Scientist - Machine Learning/Artificial Intelligence

What is in it for you?

- Understand business requirements, analyze and extract relevant information from large amounts of historical data.

- Use your knowledge of Information retrieval, NLP, Machine Learning (including Deep Learning) to build prototype solutions keeping scale, speed and accuracy in mind.

- Work with engineering teams to implement the prototype. Work with engineers to design appropriate model performance metrics and create reports to track the same.

- Work with the engineering teams to identify areas of improvement, jointly develop research agenda and execute on the same using cutting edge algorithms and tools.

- You will need to understand a broad range of ML algorithms and appreciation on how to apply them to complex practical problems. You will also need to have enough theoretical background and a good grasp of algorithms to be able to critically evaluate existing ML algorithms and be creative when there is a need to go beyond textbook solutions.

Who should apply for this role ?

- PhD/Research Degree or BS/MS in Computer Science, Statistics, Artificial Intelligence, Machine learning, Operations Research or related field.

- 1 - 4 years of experience in building Machine Learning/AI/Information Retrieval models

- Extensive knowledge and practical experience in machine learning, data mining, artificial intelligence, statistics.

- Understanding of supervised and unsupervised algorithms including but not limited to linear models, decision trees, random forests, gradient boosting machine etc.

- Excellent analytical and problem-solving abilities.

- Good knowledge of scientific programming in Python.

- Experience with Apache Spark is desired.

- Excellent verbal & written communication skills

Who should apply for this role ?

- PhD/Research Degree or BS/MS in Computer Science, Statistics, Artificial Intelligence, Machine learning,

Operations Research or related field.

- 1 - 4 years of experience in building Machine Learning/AI/Information Retrieval models

- Extensive knowledge and practical experience in machine learning, data mining, artificial intelligence, statistics.

- Understanding of supervised and unsupervised algorithms including but not limited to linear models, decision trees, random forests, gradient boosting machine etc.

- Excellent analytical and problem-solving abilities.

- Good knowledge of scientific programming in Python.

- Experience with Apache Spark is desired.

- Excellent verbal & written communication skills