DATA SCIENTISTS

- Understand data and different platforms used by client

- Translate business requirements from the client into equivalent modeling tasks

- Actively manage & lead ongoing predictive modeling assignments

- Engage with client, understand requirements & suggest predictive modeling/ML solutions

- Responsible for building and improving Recommendation Engines, Propensity Modeling etc.

- Test / Validate / Measure Performance of various statistical and data science models

- Use statistical concepts like ROC curve, Lift Analysis to evaluate models and predict performance of data science models and other experiments in production

- Provide expertise to the organization on statistical techniques and their usage and help with analysis on various datasets and analysis of A/B experiments

- Build and manage a team of data scientists, data analysts and data product managers.

- Liaise with data engineers on building data marts, reports, data warehouse, data pipelines and data tracking mechanisms.

- Conduct case studies and effectively communicate findings to establish cause & effect relationships from data analysis and separate causation from correlation

- Evangelize the need for data science across the organization and educate peers and other leaders in the company of the latest in data science and analytics

- Understand the underlying data architecture such as schemas and table relationships for data extraction and configuring new reports.

- Able to work with large volumes of user demographic and activity data

- Ensure thorough quality check of the output from team and provide tangible insights / recommendation to the client.

- Understand data and different platforms used by client

- Translate business requirements from the client into equivalent modeling tasks

- Actively manage & lead ongoing predictive modeling assignments

- Engage with client, understand requirements & suggest predictive modeling/ML solutions

- Responsible for building and improving Recommendation Engines, Propensity Modeling etc.

- Test / Validate / Measure Performance of various statistical and data science models

- Use statistical concepts like ROC curve, Lift Analysis to evaluate models and predict performance of data science models and other experiments in production

- Provide expertise to the organization on statistical techniques and their usage and help with analysis on various datasets and analysis of A/B experiments

- Build and manage a team of data scientists, data analysts and data product managers.

- Liaise with data engineers on building data marts, reports, data warehouse, data pipelines and data tracking mechanisms.

- Conduct case studies and effectively communicate findings to establish cause & effect relationships from data analysis and separate causation from correlation

- Evangelize the need for data science across the organization and educate peers and other leaders in the company of the latest in data science and analytics

- Understand the underlying data architecture such as schemas and table relationships for data extraction and configuring new reports.

- Able to work with large volumes of user demographic and activity data

- Ensure thorough quality check of the output from team and provide tangible insights / recommendation to the client.