About the Role
As a Data Scientist at HuntingCube, you will be working with a dynamic team of Business stakeholders, Data Engineers, and other Data Scientists. Your role will involve guiding the Data Engineering team, performing in-depth data analysis, and implementing robust AI/ML pipelines.
Responsibilities
- Work with the team of Business stakeholders, Data Engineers and Data Scientists.
- Guide Data Engineering team to extract datasets and apply relevant transformations for specific problem statements.
- Work independently to perform Data profiling, Exploratory Data Analysis and Data completeness checks to use it well with AI/ML algorithms.
- Work with project stack holders to understand the business problems and apply feature engineering to prepare the relevant data signals for model training and model improvement.
- Implement robust AI/ML pipeline which can perform operations like - Data Cleaning, Data Transformation, Feature Engineering, Model Training at scale, Evaluate and Improvement and Serving.
- Work with ML engineers to deploy the AI/ML models to scalable production system with Kubernetes platform.
- Monitor and improve the models periodically.
Requirements
- Efficient in Python Programming language, Pandas, SQL.
- Having knowledge of Statistics, Machine Learning - Regression, Classification and Clustering, Deep Learning - RNN, CNN, Transformers.
- Experience working with End to End Machine Learning project Life cycle.
- Experience working over one of the ML Frameworks - SKLearn, XGBoost, PyCaret and Deep Learning Frameworks - Tensorflow, PyTorch.
- Experience working over ML pipelines for Model training and Model inferencing.
- Able to work over data profiling to understand and debug inefficiency of algorithms.
- Able to work over datasets to identify the insights by performing statistical techniques with EDA.
- Prior experience of building Recommender System and Search for eCommerce domain would be a plus.