Senior Data Scientist

Reposted 8 Days Ago
Taylor, TX, USA
In-Office
90K-175K Annually
Mid level
Computer Vision • Hardware • Mobile • Software • Semiconductor
The Role
Build and optimize PySpark pipelines to ingest, clean, and transform high-volume manufacturing time-series data. Design end-to-end ML pipelines for feature engineering, training, validation, deployment, and monitoring. Implement and tune anomaly detection and root-cause models, manage model lifecycle (versioning, retraining, rollback), and set up alerts and data quality checks to ensure production reliability.
Summary Generated by Built In

About Samsung Austin Semiconductor
Samsung is a world leader in advanced semiconductor technology, founded on the belief that the pursuit of excellence creates a better world. At Samsung Austin Semiconductor, we are Innovating Today to Power the Devices of Tomorrow. 

Come innovate with us!

Position Summary

As a Senior Data Scientist at Samsung Austin Semiconductor, you will build and deploy machine learning systems that directly improve our semiconductor manufacturing process. Your work will center on anomaly detection, root cause analysis, and virtual metrology. You will spend most of your time working with high-frequency time-series and tabular data, engineering features, training models, and ensuring your results are clear and actionable for process engineers. You will own the full model lifecycle: data preparation, algorithm selection, deployment, monitoring, and ongoing tuning.
The team operates in a collaborative, sprint-driven environment where you will have the autonomy to design your own technical approaches, test new methods, and iterate quickly based on feedback. Prior semiconductor experience is helpful but not required; you will learn the domain through hands-on projects and direct support from the team.

Role and Responsibilities

Here’s What You’ll Be Responsible For:

  • Build supervised machine learning models for anomaly detection using high-frequency tabular and time-series data.
  • Enhance data collection and processing workflows to create robust, high-quality test datasets that ensure model accuracy, relevance, and integrity.
  • Design, train, and iterate on predictive models that integrate various process and quality data sources emphasizing algorithm selection, feature engineering, and rigorous model validation.
  • Engineer features from continuous time-series streams, combine process variables meaningfully, and build reliable methods for handling missing or sparse data.
  • Manage the full modeling workflow including cross-validation, hyperparameter tuning, experiment tracking, model versioning, and automated retraining schedules.
  • Set clear statistical benchmarks for model performance and monitor deployed models in production.
  • Communicate complex technical findings to both fellow data scientists and process engineers.

Skills and Qualifications

Here's what you'll need:


Required

  • Bachelor’s degree or higher in Data Science, Statistics, Computer Science, Physics, or a related quantitative field (Master’s or PhD preferred).
  • 5+ years of professional experience designing, training, and deploying machine learning models.
  • Solid working knowledge of regression, classification, ensemble methods, feature engineering, and model evaluation metrics.
  • Advanced proficiency in Python for data analysis and modeling, plus strong SQL skills for extracting and transforming large datasets.
  • Experience building and maintaining ML pipelines for experiment tracking, model versioning, automated retraining, and live performance monitoring.

Preferred

  • A track record of turning open-ended questions into clear machine learning problems and delivering models that run reliably in production.
  • Hands-on experience with tabular data techniques like categorical encoding, missing value imputation, and model interpretability methods such as SHAP.
  • Comfort working in an Agile environment where you can prototype quickly, validate results with real data, and refine models based on direct feedback from engineering teams.
  • Practical experience using PySpark to process, transform, and scale large datasets for machine learning workflows.

The current base salary range for this role is between $90,000 - $174,500. Individual base pay rates will depend on factors including duties, work location, education, skills, qualifications and experience. Total compensation for this position will include a competitive benefits package and may include participation in company incentive compensation programs, which are based on factors to include organizational and individual performance.

Total Rewards
At Samsung Austin Semiconductor, base pay is just one part of our total compensation package. The base compensation for this role will depend on education, experience, skills, and location.


We offer a comprehensive benefits package, including:

  • Medical, dental, and vision insurance
  • Life insurance and 401(k) matching with immediate vesting
  • Onsite café(s) and workout facilities
  • Paid maternity and paternity leave
  • Paid time off (PTO) + 2 personal holidays and 10 regular holidays
  • Wellness incentives and MORE
     

Eligible full-time employees (salaried or hourly) may also receive MBO bonuses based on company, division, and individual performance.


All positions at Samsung Austin Semiconductor are full-time on-site.


Trade Secrets
 By submitting an application, you agree not to disclose to Samsung or induce or encourage Samsung to use any confidential or proprietary information (including trade secrets) belonging to a current or former employer or other entity.


* Please visit Samsung membership to see Privacy Policy, which defaults according to your location. You can change Country/Language at the bottom of the page. If you are European Economic Resident, please click here.


* Samsung Electronics America, Inc. and its subsidiaries are committed to Equal Employment Opportunity for all individuals regardless of race, color, religion, gender, age, national origin, marital status, sexual orientation, gender identity, status as a protected veteran, genetic information, status as a qualified individual with a disability, or any other characteristic protected by law.

Skills Required

  • Bachelor's degree or higher in Computer Science, Software Engineering, Data Science, or related quantitative field.
  • 3-5+ years professional experience building and maintaining machine learning systems.
  • Strong proficiency in PySpark and distributed data processing, including job optimization techniques.
  • Hands-on experience with Python ML libraries (scikit-learn, TensorFlow, PyTorch, or XGBoost).
  • Practical knowledge of MLOps practices: pipeline orchestration, model versioning, experiment tracking, and deployment.
  • Experience setting up monitoring and alerting for data pipelines and deployed models.
  • Familiarity with on-prem or private cloud infrastructure, cluster management, and secure artifact storage.
  • Experience setting up model registries, automated retraining triggers, and rollback procedures.
  • Experience writing automated tests and validation checks for data pipelines and model outputs.

Samsung Electronics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Samsung Electronics and has not been reviewed or approved by Samsung Electronics.

  • Parental & Family Support — Paid parental leave of up to 14 weeks is offered in U.S. entities, alongside family‑building support, caregiver resources, and adoption assistance. Semiconductor sites note fully paid parental leave for eligible employees and targeted programs for pregnancy and infant care.
  • Leave & Time Off Breadth — Generous PTO equivalent to about 20 days per year for full‑time U.S. employees, increasing with tenure, is paired with company holidays. Some entities also promote flexible time initiatives and paid volunteer time.
  • Retirement Support — Semiconductor units publicly detail a 401(k) match with immediate vesting, and other U.S. entities highlight strong retirement support. Additional financial programs such as student‑loan repayment and charitable‑gift matching bolster long‑term savings.

Samsung Electronics Insights

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The Company
HQ: Suwon-si
145,454 Employees
Year Founded: 1969

What We Do

Samsung Electronics is a global leader in technology, opening new possibilities for people everywhere. Through relentless innovation and discovery, we are transforming the worlds of TVs, smartphones, wearable devices, tablets, digital appliances, network systems, medical devices, semiconductors and LED solutions. Samsung is also leading in the Internet of Things space through, among others, our Smart Home and Digital Health initiatives. Since being established in 1969, Samsung Electronics has grown into one of the world’s leading technology companies, and become recognized as one of the top 10 global brands. Our network now extends across the world, and Samsung takes great pride in the creativity and diversity of its talented people, who drive our growth.

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