Senior Data Scientist

Posted 7 Hours Ago
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Yokneam
In-Office
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Seeking a Senior Data Scientist to develop AI solutions, implement ML models, optimize performance, and collaborate across teams to solve complex manufacturing challenges.
Summary Generated by Built In

We are looking for an expert data scientist to join the product engineering data science team and help us compose our AI solutions, production test predictions, yield forecasting, unsupervised learning, characterization predictions, and anomaly detection across the design and manufacturing process. As a Senior Data Scientist, you will research, develop, implement, and maintain intelligent algorithms and systems driven by learning algorithms and deep neural architectures. You will collaborate directly with different business teams, including data scientists, data engineers, software engineers, and product managers, to drive innovation and ground-breaking solutions. If you genuinely passionate about data science, has a strong background in data research, programming, and possesses excellent problem-solving we'd love to hear from you!

What you’ll be doing:

  • Develop and implement machine learning & deep learning models: Compose research, develop, and deploy scalable models and algorithms that address sophisticated business challenges in the manufacturing process. Apply various methods including supervised and unsupervised learning.

  • Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the models' performance.

  • Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning.

  • Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure detailed deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.

  • Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

What we need to see:

  • Master’s degree in Computer Science, Information Systems, Engineering, Statistics, or a related field.

  • 5+ years of experience as a data scientist or a similar role, with a consistent record of successfully delivering ML / DL solutions.

  • Demonstrated expertise in conducting clustering research.

  • Experience with training models over tabular data.

  • Strong programming skills in languages such as Python, R, or Java. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.

  • Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib.

  • Deep understanding of machine learning algorithms, statistical models, and data structures.

  • Familiarity with software development practices and version control systems (e.g., Git).

  • Experience with experimental design, A/B testing, and evaluation metrics for ML models.

Ways to stand out from the crowd:

  • Strong analytical thinking and problem-solving abilities, with a focus on applying ML techniques to real-world challenges.

  • Ability to analyze complicated and wide data sets, identify patterns, and derive significant insights.

  • Experience with Large Language Models (LLM) and Natural Language Processing (NLP).

  • Self-motivated with a goal to stay updated on the latest methodologies and machine learning technologies.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

Top Skills

Java
Matplotlib
Numpy
Pandas
Python
PyTorch
R
Scikit-Learn
TensorFlow
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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