Business and Marketing Data Scientist, gTech Ads (Mandarin, English)

Google

Google is a global technology company that powers the open internet with advertising technology and products.

Shanghai, China • Beijing, China

Data

Mid-Level Software Engineer

In-Person

3+ years of experience

Description For Business and Marketing Data Scientist, gTech Ads (Mandarin, English)

Google's gTech Ads team is seeking a Business and Marketing Data Scientist to join their dynamic organization responsible for support and technical services across the Ad products stack. This role combines technical expertise in data science with client-facing responsibilities, requiring both analytical and communication skills. The position offers an opportunity to work with Google's advertising products while helping customers optimize their marketing effectiveness.

The role involves leading data science initiatives in marketing effectiveness and portfolio management, requiring strong ML and statistical knowledge. You'll collaborate directly with customers to understand their challenges, develop modeling frameworks, and translate complex data insights into actionable business recommendations. This position is perfect for someone who can bridge the gap between technical analysis and business strategy.

As part of Google's advertising ecosystem, you'll work on products that connect people, publishers, and advertisers across the open internet. The role offers exposure to various advertising domains including search, display, shopping, travel, and video advertising, as well as analytics. You'll be part of a global team that ensures customers get the best ROI while maintaining Google's position as a trusted partner.

The ideal candidate will have a Master's degree in a quantitative field, strong programming skills in Python and SQL, and the ability to communicate fluently in both Mandarin and English. This position offers the opportunity to work with cutting-edge technology while making a significant impact on Google's advertising business and its clients' success. You'll be part of a team that values innovation, collaboration, and data-driven decision making, while working on solutions that scale from small businesses to large enterprises.

Last updated 3 months ago

Responsibilities For Business and Marketing Data Scientist, gTech Ads (Mandarin, English)

Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management, with knowledge of ML and statistics
Collaborate with customers to unpack their problems and identify the best statistical techniques that can solve the problem, own the development of a modeling framework
Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a larger solution
Collaborate with customers and internal teams to translate data and model results into tactical insights that are actionable for decision-making. Co-present to and work with clients to integrate recommendations into business processes
Collaborate with Product/Engineering teams to increase and optimize capabilities of our Applied team, employing methods which create opportunities for scale, proactively helping to drive innovation

Requirements For Business and Marketing Data Scientist, gTech Ads (Mandarin, English)

Python

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience
3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis
Ability to communicate in Mandarin and English fluently to support client relationship management in this region

Google

Google is a global technology company that powers the open internet with advertising technology and products.

Shanghai, China • Beijing, China

Data

Mid-Level Software Engineer

In-Person

3+ years of experience

Google

Find Winner on a Tic Tac Toe Game

Data Structures & AlgorithmsEasy

Tic-tac-toe is played by two players A and B on a 3 x 3 grid. The rules of Tic-Tac-Toe are: Players take turns placing characters into empty squares ''. The first player A always places 'X' characters, while the second player B always places 'O' characters. 'X' and 'O' characters are always placed into empty squares, never on filled ones. The game ends when there are three of the same (non-empty) character filling any row, column, or diagonal. The game also ends if all squares are non-empty. No more moves can be played if the game is over. Given a 2D integer array moves where moves[i] = [rowi, coli] indicates that the ith move will be played on gridrowi. return the winner of the game if it exists (A or B). In case the game ends in a draw return Draw. If there are still movements to play return Pending. You can assume that moves is valid (i.e., it follows the rules of Tic-Tac-Toe), the grid is initially empty, and A will play first. For example: moves = [[0,0],[2,0],[1,1],[2,1],[2,2]] Output: A moves = [[0,0],[1,1],[0,1],[0,2],[1,0],[2,0]] Output: B moves = [[0,0],[1,1],[2,0],[1,0],[1,2],[2,1],[0,1],[0,2],[2,2]] Output: Draw

Arrays

Google

Design a URL shortening system.

System DesignMedium

Let's design a system for URL shortening, like TinyURL. Assume that we need to handle a large number of requests, say billions of URLs per day. Consider the following: Functional Requirements: The system should generate a shorter, unique alias for a given URL. Users should be able to enter a shortened URL and be redirected to the original URL. The shortened URLs should be relatively short. Non-Functional Requirements: The system should be highly available. URL redirection should be as fast as possible. The shortened URLs should be unique. The system should be scalable to handle a large number of URLs and requests. Considerations: How would you design the data model to store the mappings between shortened and original URLs? What algorithms would you use to generate the shortened URLs? Consider the trade-offs between different algorithms. How would you handle collisions (when the same shortened URL is generated for two different original URLs)? What kind of database would you use and why? How would you handle the high volume of traffic and ensure low latency for redirection? Consider caching strategies. How would you scale the system to handle future growth? Walk me through your design, explaining your choices and the rationale behind them. Include diagrams and specific technologies where appropriate. Explain how you would ensure the system meets the requirements for availability, performance, and scalability.

Database Problems

Arrays

Strings

Google

Where do you see yourself in 5 years?

Behavioral

Where do you see yourself in 5 years?

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