Data Scientist

1 week ago

Oakland, United States Cynet Systems Full time
Job Description:

Pay Range: $91.98hr $96.98hr

Responsibilities:
  • Leads conversations with business stakeholders and subject matter experts to understand business and subject matter context.
  • Scopes and prioritizes modeling work to deliver business value.
  • pplies data science, machine learning and other analytical modeling methods to develop defensible and reproducible predictive models.
  • Serves as the technical lead for the development of computer vision models, leading data labeling, model training and model evaluation.
  • Extracts, transforms, and loads data from dissimilar sources from across Client for model-building and analysis.
  • Writes and documents python code for data science (feature engineering and machine learning modeling) independently.
  • Documents and presents data science experiments and findings clearly to other data scientists and business stakeholders.
  • ct as peer reviewer of models and analyses built by other data scientists.
  • Develops and presents summary presentations to business.
  • Present findings and makes recommendations to officers and cross-functional management.
  • Build and maintain strong relationships with business units and external agencies.
  • Works with cross functional teams, including data engineers, machine learning engineers, data scientists, and subject matter experts.
Education Minimum:
  • Bachelor's degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
Education Desired:
  • Master's degree in one of the above areas.
Experience Minimum:
  • 4 years in data science for business (or 2 years, if possess master's degree, as described above).
Knowledge, Skills, Abilities and Technical Competencies:
  • Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them.
  • Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment.
  • Competency in commonly used data science and/or operations research programming languages, packages, and tools.
  • Hands-on and theoretical experience of data science/machine learning models and algorithms.
  • bility to synthesize complex information into clear insights and translate those insights into decisions and actions.
  • Demonstrated ability to explain in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
  • Competency in the mathematical and statistical fields that underpin data science.
  • Mastery in systems thinking and structuring complex problems.
  • bility to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies.
Desired:
  • Experience building computer vision models.
  • Experience with AWS technologies (S3, Ground Truth, Sagemaker).

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