Data Scientist

Job Summary

Utilizes their analytical, statistical and programming skills to collect, analyze and interpret large sets of data. Creates various machine learning-based data models to develop data driven solutions to complex business problems. Responsible for understanding the business change needs, accessing the impact of future changes & capture & analyze data. 

Job Responsibilities 1

• Executes analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
• Identifies relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
• Devises and utilizes algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy.
• Analyzes data for trends and patterns and Interprets data with a clear objective in mind.
• Implements analytical models into production by collaborating with software developers and machine learning engineers.
• Communicates analytic solutions to stakeholders and implement improvements as needed to operational systems
• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

Job Responsibilities 2

1. Works as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.
2. Mine and analyze data from company databases to drive optimization and improvement of business strategies.
3. Assess the effectiveness and accuracy of new data sources and data gathering techniques.
4. Develop custom data models and algorithms to apply to data sets.
5. Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
6. Coordinate with different functional teams to implement models and monitor outcomes.
7. Develop processes and tools to monitor and analyze model performance and data accuracy.