Senior Data Scientist (Enterprise DS & AI Org - 14+ ...

The responsibilities of these positions include:Leads conversations with business stakeholders and subject matter experts to understand business and subject matter contextScopes and prioritizes modeling work to deliver business valueApplies data science, machine learning and other analytical modeling methods to develop defensible and reproducible predictive modelsServes as the technical lead for the development of computer vision models, leading data labeling, model training and model evaluationExtracts, transforms, and loads data from dissimilar sources from across for model-building and analysisWrites and documents python code for data science (feature engineering and machine learning modeling) independentlyDocuments and presents data science experiments and findings clearly to other data scientists and business stakeholders.Act as peer reviewer of models and analyses built by other data scientistsDevelops 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 expertsEducation 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 (or 2 years, if possess a 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 andor operations research programming languages, packages, and tools.• Hands-on and theoretical experience of data sciencemachine 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 scienceartificial intelligencemachine learning techniques and technologies • Desired: experience building computer vision models• Desired: experience with AWS technologies (S3, GroundTruth, Sagemaker)

Created: 2025-02-24