Responsibilities
- Research and implement appropriate ML algorithms and tools
- Develop machine learning applications according to requirements
- Select appropriate datasets and data representation methods
- Train ML/AI algorithms and test them for accuracy, precision and recall.
- Perform statistical analysis and fine‑tuning using test results
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
Job Profile:
- BachelorsDegree in Computer Science or related field required
- Minimum 2 years experience designing and implementing time series forecasting.
- Minimum 2 years experience designing and implementing machine learning solutions including supervised and unsupervised models.
- Object oriented programming skills in one of Scala, Java, Python, C++.
- Strong knowledge and understanding of machine learning pipelines from standardization, normalization, clustering, modeling, scoring, validation
- Time series forecasting using regressions models and Recurrent Neural Networks (RNN) including LSTM .
- Common data science toolkits, such as NumPy Pandas scikit-learn Matplotlib etc.
- Deep learning frameworks such as PyTorch TensorFlow
- Good scripting and programming skills
- Processing, cleansing, and verifying the integrity of data used for analysis
- Creating automated anomaly detection systems and constant tracking of its performance
- SQL and NoSQL databases such as PostgreSQL Cassandra MongoDB etc. is a plus
- Past history with AWS is a plus
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