Senior Data Scientist
Samsung Electronics is hiring a Senior Data Scientist. It pays $90k-$175k a year and Level rates it ; you can apply on Samsung Electronics.
Level's read on this job
- Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
- Tools and skills the posting cites include AI evaluation.
- Level classifies it as a senior role.
- Level lists 657 other open roles at Samsung Electronics.
AI in this role
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.
How we rate this
Senior Data Scientist at Samsung Electronics rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- This job starts at
- $90k
- Typical data scientist job
- $165k
This posting starts 45% below the typical data scientist job. See data scientist jobs
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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