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Support Uber’s rapidly growing and unique safety and insurance operations!. Build and own periodic reporting - Take advantage of the ever-growing amount of data we have at our fingertips to...
Utilize mathematics and statistics including Probability, Advanced Calculus and Linear Algebra, Regression Analysis, and Causal Inference;. Perform Machine Learning and Data Mining by implementing Decision Trees, Random Forests, XGBoost Machine...
Work with partners across Digital & Customer Experience functions and LOB’s to provide data driven insights to support Digital strategic direction and growth. Provide consultative support for Digital Product partners...
Categorize and organize data for evaluating and identifying sourcing opportunities by querying data from purchase tools utilizing advanced Excel functions;. Create analytics requirements to make data report-ready;. Develop and deliver...
Acquire and manipulate data using SQL, R, Python or Excel for data wrangling, data cleaning, sourcing from applications relational databases, and Splunk;. Create data visualizations using Excel, Tableau or Power...
DESCRIPTIONIn this role, you will support up to various data science decision meetings for device companion product based on various factors, such as device price, inventory, traffic, economical, inflation, and...
:Minimum Requirements: Master’s degree, or foreign equivalent, in Management Science, Information Systems, Engineering, or a closely related field plus two years of experience in the job offered or a related...
Support Uber’s rapidly growing and unique safety and insurance operations!. Build and own periodic reporting - Take advantage of the ever-growing amount of data we have at our fingertips to...
Data Scientists are responsible for analyzing and interpreting large and complex datasets to uncover insights that inform business decisions and drive innovation. They use a combination of statistical and machine learning techniques, as well as programming languages such as Python and R, to extract, clean, and transform data. They also use tools such as SQL, Hadoop and Spark to work with large datasets and perform data analysis.
Data Scientists work closely with cross-functional teams, such as product managers, marketing and operations, to understand their specific data needs and provide them with insights to make informed decisions. They also collaborate with data engineers to build and maintain the infrastructure necessary for data analysis. They also use data visualization tools such as Tableau and Power BI to create interactive dashboards and reports to communicate data insights clearly and effectively to non-technical stakeholders.