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).