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# Machine Learning Engineer - Data Science

- **Company:** Samsung
- **Location:** Mountain View, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Computer Programming, Databases, Data Mining, Python (Programming Language), Machine Learning, Tensorflow, Oop Languages, Software Engineering, SQL Databases, Pytorch, Apache Spark, Scikit Learn, Data Analytics, Data Management
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25304_926f6e272ecb2acae40cd96d891864b2

## About the Role

* Master's or PhD degree in science or engineering fields. 4+ years of industry experience with a Master's degree or 2+ 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 $230,000 and $280,000. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.

## Description

* Lead a data science team to provide data-driven insights and deliver production-grade solutions to maximize the value of our data.
 * Innovatively examine the 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 various audiences, such as the leadership team, engineering stakeholders, and product owners.
 * Promote a data-driven culture within the company by coaching different stakeholders.