Engineer III, Machine Learning Software

Position Summary

Role and Responsibilities

Job Description:

Work as a tech lead to deliver production-grade solutions, maximizing data value and optimizing our systems. Develop optimization and machine learning solutions for various components of the ad serving system, including but not limited to targeting, pacing, pricing, and bidding. Drive business growth by proposing and delivering end-to-end data science projects into production. Proactively analyze the business health of the Samsung Ads ecosystem, identify product bottlenecks, uncover new business opportunities, support strategic decision-making, and propose technical solutions. Develop metrics and measurement frameworks to assess machine learning models, attribution, incrementality testing, and campaign performances. Communicate effectively and present to diverse audiences, including leadership teams, engineering stakeholders, and product owners.

Minimum Education & Experience Requirements:

Master's degree in Computer Science, Mathematics, Statistics, a related field, or a foreign equivalent plus 3 years of post-baccalaureate experience in job offered or any data science related job titles.

Applicants must have at least 3 years of experience in the following: (1) Data Wrangling & Integration including identifying, accessing, and integrating diverse data sources, including proactively addressing data limitations and extending data applicability; (2) Applying statistical theories and methodologies, including hypothesis testing, regression analysis, Bayesian methods, causal inference, time series analysis, and experimental design (A/B testing); (3) Data Modeling including transforming raw data into features and feature engineering techniques, including variable transformation, bucketization, and creation of calculated variables; (4) Full lifecycle of Machine Learning model development - from feature engineering to production deployment. Proficiency in a wide range of algorithms (DNNs, RNNs, LSTMs, Gradient Boosting, XGBoost, SVMs, Logistic Regression) and the ability to select the optimal approach for a given problem, experience in model validation, including bias detection and error analysis; (5) hands-on coding in Python, SQL, shell scripting, Big Data Technologies including experience with Spark and AWS data processing services, and data manipulation libraries (Pandas, NumPy, Scikit-learn); and (6) applying data structures and algorithms, object-oriented design to produce efficient and maintainable production code.

The salary range for this role is expected to be between $225,077 - $235,077/Year. Actual pay will be determined considering factors such as relevant skills and experience, and comparison to other employees in the role.

No sponsorship available for this position.

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Skills and Qualifications

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