Data Scientist / Sr. Data Scientist

Claim Genius

For applying as a Sr. Data Scientist, the person should have overall 7-8 years of experience out of which 4-5 years of experience should be in Machine & Deep Machine learning. Especially using Convolution Neural Network (CNN), Image Analytics TensorFlow, Open CV etc.

For applying as just a data scientist (Junior), the person needs to have experience of 3 9 years.

With our fast-growing data scientists team, we are looking to hire self-motivated smart individuals who are willing to take challenges in the field of AI predictive image analytics & machine learning.

Responsibilities

The Machine & Deep Machine Learning Software Engineer (Expertise in Computer Vision) will be an early member of a growing team with responsibilities for designing and developing highly scalable machine learning solutions that impact many areas of our business.

The individual in this role will help in the design and development of Neural Network (especially Convolution Neural Networks) & ML solutions based on our reference architecture which is underpinned by big data & cloud technology, micro-service architecture and high performing compute infrastructure.

Typical daily activities include contributing to all phases of algorithm development including ideation, prototyping, design, and development production implementation.

Required Skills

An ideal candidate will have background in software engineering and data science with expertise in machine learning algorithms, statistical analysis tools, and distributed systems.

Experience in building machine learning applications, and broad knowledge of machine learning APIs, tools, and open source libraries

Strong coding skills and fundamentals in data structures, predictive modelling and big data concepts

Experience in designing full stack ML solutions in a distributed compute environment

Experience working with Python, Tensor Flow, Keras, Sci-kit, pandas, NumPy, AZURE, AWS GPU

Excellent communication skills with multiple levels of the organization,