Data Scientist 1
at Global internet of things connected solutions provider(H1)
Data Science
Machine Learning (ML)- 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 the business.
- 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.
Key Criteria:
- 2+ 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 modeling is desirable.
- Proficiency in programming skills involving Python, C/C++, and Python Data Science Stack (NumPy, SciPy, Pandas, Scikit-learn, Jupyter, IPython).
- Experience working with Amazon SageMaker or Azure ML Studio for deployments is a plus.
- Experience in data visualization software such as Tableau, ELK, etc is a plus.
- Strong analytical, critical thinking, and problem-solving skills.
- 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 skills
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