3038 Java Engineer Data Science Platform jobs in Chicago,IL

Bachelor's Degree in Computer Science or related field
A minimum 10+ years' experience in information technology or in lieu of degree, High School/GED and 15+ years of Information technology experience
A minimum of 8 years of progressive experience in governance role supporting engineering org or senior data architecture roles within regulated environments, with preference for financial services
Proven experience owning data platform architecture governance and control frameworks and driving compliance activities from design through implementation and evidence
Strong collaboration skills to work effectively with architects, engineers, risk, and audit teams
Experience managing audit coordination and regulatory compliance activities for technology platforms
Knowledge of industry best practices in data architecture and governance, with focus on cloud modernization initiatives
Strong communication skills, including ability to brief executive leadership on risk and compliance matters
Familiarity with risk management and issue tracking tools and processes is preferred
Ability and flexibility to travel for business as required

Performance Test Engineer

The Judge Group

Chicago, IL 60290

Jobot

Chicago, IL 60290

CME Group

Chicago, IL 60290

Aristek Consulting

Chicago, IL 60290

Ulta Beauty

Bolingbrook, IL 60440

2+ years of professional experience in data science, machine learning, or analytics functions, with a track record of owning and delivering work in a production environment
Advanced degree in a highly quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Economics, etc. Equivalent professional experience will be considered.
In-depth knowledge and experience with data science and machine learning concepts (e.g., multivariate regression, statistical inference, supervised and unsupervised learning, etc.)
Proficiency in Python and scientific related frameworks (e.g., Scikit-Learn, NumPy, SciPy etc.)
Hands-on experience designing, deploying, and maintaining machine learning pipelines