Data Scientist

Octro Inc

Octro Inc. is looking for a Data Scientist who will support the product, leadership and marketing teams with insights gained from analyzing multiple sources of data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.

They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights.

They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Responsibilities :

- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.

- Mine and analyze data from multiple databases to drive optimization and improvement of product development, marketing techniques and business strategies.

- Assess the effectiveness and accuracy of new data sources and data gathering techniques.

- Develop custom data models and algorithms to apply to data sets.

- Use predictive modelling to increase and optimize user experiences, revenue generation, ad targeting and other business outcomes.

- Develop various A/B testing frameworks and test model qualities.

- Coordinate with different functional teams to implement models and monitor outcomes.

- Develop processes and tools to monitor and analyze model performance and data accuracy.

Qualifications :

- Strong problem solving skills with an emphasis on product development and improvement.

- Advanced knowledge of SQL and its use in data gathering/cleaning.

- Experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.

- Experience working with and creating data architectures.

- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

- Excellent written and verbal communication skills for coordinating across teams.