Position Summary

Samsung Ads is a rapidly growing advanced advertising technology company. It focuses on enabling brands to connect with Samsung TV audiences as they are exposed to digital media by using the industry’s most comprehensive data to build the world’s most innovative advertising platform. Being part of an international company such as Samsung and doing business worldwide means working on the most challenging projects with stakeholders and teams around the globe.

We are proud to have built a world-class organization grounded in an entrepreneurial and collaborative spirit. Working at Samsung Ads offers one of the best environments in the industry to learn just how fast you can grow, how much you can achieve, and how good you can be. We thrive on problem-solving, breaking new ground, and enjoying every part of the journey.

At Samsung Ads, we are actively distilling the maximum value out of data to drive business growth and solve complex problems. We are exploring the latest data mining and machine learning techniques to form a data-driven culture for decision-making and product design. As a data scientist of the Samsung Ads Platform Intelligence (PI) team, you will have access to unique Samsung proprietary data to address existing product challenges, uncover new revenue/profit opportunities, and build end-to-end solutions with real-world impact. You will work closely with different teams to develop insights and deliver end-to-end production solutions to drive business and technical initiatives effectively. You will also work with talented engineers and top-notch machine learning researchers on exciting projects and state-of-the-art technologies. A unique learning culture and creative work atmosphere will welcome you. This is an exciting and unique opportunity to get deeply involved in envisioning, designing, and implementing with a growing team.

Location: Mountain View, CA

Role and Responsibilities

Responsibilities

• Lead a data science team to provide data-driven insights and deliver production-grade solutions to maximize the value of our data

• Innovatively examine business health of and identify product bottlenecks in the entire Samsung Ads ecosystem to unveil new business opportunities, help strategic decision-making, and suggest technical solutions

• Propose and deliver data science projects into production from end to end to drive business growth

• Apply hands-on data science techniques, including advanced analytics, machine learning, statistics, etc. to solve challenging problems promptly

• Closely work with the machine learning team to define and improve machine learning products

• Provide data science support to various stakeholders, for example, designing experiments and evaluation metrics for different products

• Effectively communicate with and present to a variety of audiences, such as the leadership team, engineering stakeholders, and product owners

• Promote a data-driven culture within the company by coaching different stakeholders

Skills and Qualifications

Experience Requirements

• Master’s or PhD degree in science or engineering fields. 7+ years of industry experience with a Master’s degree or 5+ years of industry experience with a PhD degree

• Solid theoretical background in data analytics, data mining, machine learning, and statistics

• Outstanding problem-solving skills and creative thinking to address open challenges in various fields

• Proficiency in SQL and databases

• Strong programming skills in Python, Go, or other OOP languages

• Experience with mainstream big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.)

• Excellent communication and interpersonal skills

Preferred Experience Requirements

• Hands-on experience with production-grade machine learning solutions and/or software development

• Experience with the advertising industry and real-time bidding (RTB) ecosystem

The salary range for this role, for candidates based in California, is expected to be between $220,000 and $280,000.  Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.
 

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