We think you also hate when travel app is giving you a headache right A slight misinformation can ruin the trip.
That is exactly what we are tackling as tfam! Making sure that our 50 million users have the best experience in crafting their own adventure.
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 databased 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.
Develop custom data models and algorithms to apply to data sets.
Use predictive modeling 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 impact to business.
Mandatory belongings that you must prepare :
Min. 8years of experience in data analysis and modeling
A Bachelor in Computer Science Statistics Mathematics or another quantitative field.
Strong problem solving skills with an emphasis on product development.
Proficient in programming skills (R Python SQL etc. for data acquisition processing and analysis from large data sets.
Knowledge of data science concepts (regression classification clustering properties of distributions statistical tests and proper usage etc. and experience with applications.
Knowledge of a variety of machine learning techniques (Random forest SVM artificial neural networks etc. and their realworld advantages/drawbacks.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques.
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