Data Scientist 2 Job in Multi Recruit

Roles and Responsibility

• Required to work individually or as part of a team on data science projects and work closely with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions.
• Build quick prototypes to check feasibility and value to business.
• Building IPs and Proof of Concepts for products and projects in current or future development
• Design, training and deploying neural networks for computer vision and machine learning related problems.
• Perform various complex activities related to statistical/machine learning.
• Coordinate with business teams to provide analytical support for developing, evaluating, implementing, monitoring and executing models.
• Collaborate with technology teams to deploy the models to production.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Analyse large amounts of information to discover trends and patterns.

Key Criteria:

• 5+ years of experience in solving complex business problems using machine learning.
• Understanding and modeling experience in supervised, unsupervised and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required.
• Experience in Computer Vision/Image Processing/Pattern Recognition, Machine Learning, Deep Learning or Artificial Intelligence.
• Understanding of Deep Learning Architectures like InceptionNet, VGGNet, FaceNet, YOLO, SSD, RCNN, MASK Rcnn, ResNet.
• Experience with one or more deep learning frameworks e.g., TensorFlow, PyTorch.
• Knowledge of vector algebra, statistical and probabilistic modelling is desirable.
• Proficiency in programming skills involving Python, C/C++, and Python Data Science Stack (NumPy, SciPy, Pandas, Scikit-learn, Jupyter, IPython).
• Experience with OpenCV or other computer vision libraries
• Experience working with Amazon SageMaker or Azure ML Studio for deployments is a plus.
• Experience in building ML models that are productized in cloud and edge computing devices (IOT) is a plus.
• Experience in data visualization software such as Tableau, ELK, etc is a plus.
• Strong analytical, critical thinking and problem-solving skills.

Qualifications:

• B. E/ B.Tech./ M. E/ M. Tech in Computer Science, Applied Mathematics, Statistics, Data Science, or related Engineering field.
• Minimum 60% in Graduation or Post-Graduation
• Great interpersonal and communication skill