Data Scientist III - Product Analytics

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Data Scientist III

We are looking for an experienced Data Scientist to join the team that is working on Search and Ranking products in Lodging and Flights.
 

As a Data Scientist, you will help Search and Ranking improve. You will collaborate with a multi-disciplinary team on a wide range of problems. You will bring scientific rigor and statistical methods to the challenges of business growth and product development

What you'll do:

• Comprehend probability, frequentist vs Bayesian statistics, and how to apply to business problems (eg. AB testing, log regression output). Understanding differences between statistically signifiant test readout vs exploratory analysis.
• Apply and comprehend statistical concepts like regression, ANOVA, AB testing etc and understands the difference between a statistically significant test readout vs exploratory analysis.
• Display the ability to define and build the data appropriately (eg. linear and non-linear regression as well as using other modeling techniques such as clustering, logistic regression etc). Correctly interpreting the output and iterates and improves the model.
• Possess intermediate understanding of common data models, underlying assumptions, types of business questions they can best answer, and what data sources would best support the model (i.e. linear and logistic regression).
• Show initiative to learn new model approaches and techniques and apply those learnings to current projects.
• Understand advanced business domain and use this knowledge to refine the question at the heart of the model project, drive model design decisions (i.e. model selection, feature engineering), and provide recommendations (model improvements, business changes, AB tests, further analysis etc).
• Demonstrate an understanding of technical information to understand and synthesize different data sources and create basic data pipelines and workflows to support the model. Consider legal implications and seek out clarification and solutions if applicable.
• Values process and creates shareable code and documentation to share with wider team on tools like github, IEX, confluence.
• Creates clear visualizations that support the data story and deepen the audience's understanding.
•  Provide constructive feedback to help up-skill teammates in this area.
• Build trust and work collaboratively and transparently with stakeholders. Seeks out analytics teammates for peer reviews, brainstorming and other upskilling and improves their own skills by doing the same for both junior and senior teammates
• Ability to tell a story in a clear and concise way and present insights rather than just data. Seeks feedback from manager/peers/stakeholder partners early on and demonstrates ability to action the feedback on current and future projects.
• Display advanced domain ( i.e., travel, online retail) knowledge, business acumen (understanding the underlying business objectives) and critical reasoning skills
• Possesses strong knowledge and understanding of the organization's processes, objectives, and challenges and their impact on the business, and is not easily deterred if there are barriers in sharing the results/effecting change. 

• Work with big data and understand potential challenges and solutions and ability to explain this to both technical and non technical partners  with minimal guidance from manager / senior peers.
• Can write new / understand existing advanced SQL such as creating views and tables, use of partitions, advanced SQL functions (e.g. RANK() Over, PARTITION BY), and is familiar with different flavors of SQL (e.g.  presto/hive/postgresql ), querying tools (e.g. qubole/big query/hadoop), and concepts such as Store Procedures, Cursors and Temp tables.
• Possess intermediate level knowledge of the most important data sources to their work area and the wider business. Knows how to find information about new data sources when required and which support channels to go to in order to unblock data issues when they arise and follows through to resolution. Shares information about data issues and shares knowledge about data sources with teammates.
• Demonstrates knowledge and use of best practices for data quality checks, query cost/performance optimization and proactiv