Data Scientist Lead
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.
Your main duties in flying with us:
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
- Mine and analyze data from company 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 customer experiences, revenue generation, ad targeting and other business outcomes
- Develop company A/B testing framework and test model quality
- Coordinate with different functional teams to implement models and monitor outcomes
- Develop processes and tools to monitor and analyze model performance and data accuracy
Mandatory belongings that you must prepare:
- Have minimum 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PhD in Statistics, Mathematics, Computer Science or another quantitative field
- Strong problem-solving skills with an emphasis on product development
- Experience using statistical computer languages (R, Python, SQL, 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
- Have a drive to learn and master new technologies and techniques
In the event that you haven’t received any updates after 3 weeks, your data will be kept and we may contact you for another career destination.