- Own and execute end to end delivery of one or more than one data science model development, as per requirement provided by project/product manager
- Extract data from multiple data sources using Hadoop / SQL
- Develop, Validate and Operationalize predictive models using appropriate variables and ML/deep learning techniques
- Perform ad-hoc deep-dive analysis and generate actionable insights
- Create technical documentation and provide post-production support for a time-bound period
- Excellent knowledge of various statistical / Machine Learning / Deep Learning algorithms such as Feature Engineering/selection, Regression, Classification, Clustering, Recommendation Engine, Anomaly Detection, NLP, Reinforcement Learning, etc.)
- 2 to 4 years of hands-on expertise in developing data science models by applying above mentioned algorithms on structured / text data, using Python
- Proficient in writing optimized queries using any one of the DB query languages (Hive/Impala/SQL/MongoDB etc.).
- Knowledge of PySpark, Hadoop, MapReduce will be a big plus.
- Must have working experience in DevOps tools like Docker, Kubernetes, Jenkins, etc.
Good to Have skill sets:
- Experience across end-to-end data science project life cycle (use case framing, data collection, data exploration, design of experiments, model development, selection and deployment, post-production support)
- Self-motivated to learn different techniques/technologies, as per the project’s need and go the extra mile to bring customer delight