Data Scientist (Machine Learning) Sunnyvale Job at Asimily, Sunnyvale, CA

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  • Asimily
  • Sunnyvale, CA

Job Description

Fastest growing company and 2nd fastest growing in cybersecurity

Asimily is an IoT Security Platform. We were recognized as the 11th fastest-growing cybersecurity company by Deloitte as having an innovative market-leading security solution. With growing cybersecurity risks from IoMT devices, it is crucial to proactively manage these devices and balance patient, data, and business security and safety. Our platform streamlines risk management with comprehensive identification, assessment, vulnerability management, anomaly management, and more to accelerate enterprise risk management and recovery from downtime events. Leading healthcare organizations use Asimily to achieve digital transformation and facilitate cyber risk reduction.


About You

As a Data Scientist specializing in Machine Learning, you will be instrumental in developing and deploying predictive models and ML solutions across Asimily Platforms IoT Device Inventory, Vulnerability Management, and Threat Detection domains. This role involves crafting advanced analytical methods, machine learning algorithms to glean valuable insights from extensive and intricate datasets. You will collaborate closely with various teams to comprehend business challenges, translate them into analytical problems, and devise data-driven solutions.

Asimily provides a highly competitive cash compensation package, comprehensive benefits, and a stock option grant.

  • A Data Scientist (Machine Learning) is responsible for a variety of key tasks. These include the design and implementation of machine learning algorithms and models, as well as the development and optimization of prediction and classification systems. The role also involves analyzing large and complex datasets.
  • Core responsibilities also encompass exploratory data analysis (EDA), data cleaning, processing, and transformation, and the implementation of data pipelines and workflows.
  • Further key aspects of the role are model validation and evaluation, documenting models for reproducibility, and monitoring their performance.
  • Collaboration is vital, with the Data Scientist translating business requirements into data specifications, communicating findings to stakeholders, and participating in code reviews.

Qualifications
  • An Advanced degree in a quantitative field such as Data Science, Computer Science, Statistics, Applied Mathematics, or Computer Engineering.
  • 4+ years experience in building and deploying both supervised and unsupervised models along with a good understanding of LLM models.
  • Experience in building and deploying both supervised and unsupervised models along with a good understanding of LLM models.
  • Proficiency in programming languages like Python or R.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
  • Familiarity with data preprocessing, feature engineering, data cleaning techniques, SQL, databases, and big data technologies (e.g., Hadoop, Spark).
  • Strong understanding of statistical analysis, mathematics, and probability.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and data visualization tools (e.g., Tableau, PowerBI) is beneficial.
  • Key skills include strong problem-solving, analytical, communication, and collaboration abilities

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