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Data Scientist
3 weeks ago
As a key member of the team, you work with team to analyze and interpret data, develop metrics to measure results and integrate new methodologies.
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- Job Description
- Minimum qualifications:
PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience.
Relevant internship or work experience with data analysis.
Experience with statistical software (R, Python, S-Plus, SAS, or similar) and experience with database languages (e.g. SQL).
- Preferred qualifications:
1 year of relevant work experience, including experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
Ability to draw conclusions from data and recommend actions.
Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.
- Role and Responsibilties
Designing and implementing machine learning, information extraction, probabilistic matching algorithms and models
Using your passion for programming and deep learning/AI skills using Python, TensorFlow and deep learning frameworks like Keras, PyTorch - to solve real-life problems
Developing AI solutions in the computer vision domain using convolutional neural networks (CNN) and a combination of deep neural networks such as CNN & RNN
Solving object detection, recognition, image classification problems using machine learning and deep learning algorithms & transfer learning methods and techniques
Using innovative & automated approaches for data annotation, labeling, and data augmentation & use active learning.
Handling online code assistance, code mentoring, and education-based solutions.
Build and prototype analysis pipelines iteratively to provide insights at scale.
Research and develop analysis, forecasting and optimization methods to improve the quality of user facing products such as ads quality, search quality, end-user behavioral modeling and live experiments.
- Perks
Certificate, Letter of recommendation, Flexible work hours, Informal dress code, 5 days a week, Free snacks & beverages.