Overview
Skills
Job Details
Data Scientist, Senior Enterprise DS & AI Org
Job Level: Senior Over 15 Yes exp
Remote (work PST time zone)
Key points
- Ability 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
- Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies
- Strong in Python & R
Position Summary
Client is looking for a Data Scientist with experience in delivering data science products end-to-end. In this role, the successful candidates will be uniquely positioned at the forefront of utility industry analytics, having the opportunity to advance client s triple bottom line of People, Planet, and Prosperity. Working as part of cross functional teams, including data engineers, machine learning engineers, data scientists, and subject matter experts, this individual will lead the development of computer vision models to improve, accelerate, and automate asset inspections processes. The individual will participate in the full lifecycle of the delivery process from initial value discovery to model-building to building data products to deliver value to end users.
Education Minimum: Bachelor s degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
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
Ability 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
Ability 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
Desired: experience with AWS technologies (S3, GroundTruth, Sagemaker)