Company:
GM Financial
Location: Fort Worth
Closing Date: 20/10/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Overview:
Why GM Financial Data Science?
GM Financial Data Science focuses on communicating imporant data as part of GM Financial, the wholly owned subsidiary and captive finance arm of General Motors. Our Data Science team drives strategic decisions in the auto finance sector by bridging business functions, data science, and IT. We make data science initiatives accessible and engaging, fostering a data-driven culture.
As a Data Analyst - Graphic Designer, you will collaborate closely with both data science teams and business functions. Our team values clear communication, innovative thinking, and staying updated with industry trends. If you excel at simplifying complex concepts, creating visual narratives, and driving data-based decisions, you'll thrive here.
Joining our team means being part of a dynamic environment with opportunities to work on Azure and Adobe Cloud platforms. You'll develop skills in creating compelling visualizations and narratives, making data science impactful and understandable. If you're looking to grow your career with a forward-thinking company that values creativity and data-driven decisions, this is the place for you.
Responsibilities:
About the role
The Data Analyst-Model Management is responsible for various aspects of model management: governance, monitoring, validation and related special projects. The primary activities will be establishing best practices, ensuring compliance with existing policies and supporting model monitoring routines including migration to cloud-based tools. This position acts as a first line of defense as related to the Enterprise Model Governance policy. This position will primarily interface with model development teams, the MLOps team, and various compliance and oversight functions to ensure that model risk is managed appropriately.
Responsible for creating, maintaining, and updating model management processes for Data Science models that support model management policies
Ensure models are being routinely monitored with metrics published, interpreted, and shared
Ensure appropriate documentation and meta-data are produced from data ingestion, pre-processing, model building to deployment
Ensure operating processes and reviews are established as a timely, efficient, and effective
Continually support the development of new model monitoring processes and updating policies in accordance with GMF audit and model monitoring
Qualifications:
What makes you a dream candidate?
Knowledge of the Data Science lifecycle and steps required to develop, validate, deploy, and monitor models
Knowledge of MLOps highly desirable
Experience with data mining, data querying and knowledge of on-premise (or cloud-based) data management tools
Knowledge of statistical modeling techniques for prediction and classification
Knowledge of Operations Research methodologies for optimization and simulation
Advanced with Microsoft Excel, PowerPoint, and Word
Experience with data analysis and reporting
Understand and build SQL queries in a Data Warehouse environment and data manipulation
Run and understand code built by others for cleaning data and building statistical model in SAS and Python
Ability to work with minimal supervision
Ability to tailor different concepts to various audiences
Proficiency in Power BI development, including report and dashboard creation
Experience in Azure DevOps Agile practice
Working knowledge of Databricks platform
Experience:
Bachelor's degree in Economics, Mathematics, Statistics, Computer Science or other quantitative field; degrees in non-quantitative fields considered with adequate work experience required
Master’s Degree in in Statistics, Economics, Mathematics, Computer Science
0-2 years experience working with and querying large datasets
0-2 years experience with source code management tools like git
0-2 years experience in statistics and Machine Learning Model Governance experience
What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.
Our Culture: Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.
Compensation: Competitive pay and bonus eligibility
Work Life Balance: Flexible hybrid work environment, 2-days a week in office
#LI-hybrid
#LI-MO1
Why GM Financial Data Science?
GM Financial Data Science focuses on communicating imporant data as part of GM Financial, the wholly owned subsidiary and captive finance arm of General Motors. Our Data Science team drives strategic decisions in the auto finance sector by bridging business functions, data science, and IT. We make data science initiatives accessible and engaging, fostering a data-driven culture.
As a Data Analyst - Graphic Designer, you will collaborate closely with both data science teams and business functions. Our team values clear communication, innovative thinking, and staying updated with industry trends. If you excel at simplifying complex concepts, creating visual narratives, and driving data-based decisions, you'll thrive here.
Joining our team means being part of a dynamic environment with opportunities to work on Azure and Adobe Cloud platforms. You'll develop skills in creating compelling visualizations and narratives, making data science impactful and understandable. If you're looking to grow your career with a forward-thinking company that values creativity and data-driven decisions, this is the place for you.
Responsibilities:
About the role
The Data Analyst-Model Management is responsible for various aspects of model management: governance, monitoring, validation and related special projects. The primary activities will be establishing best practices, ensuring compliance with existing policies and supporting model monitoring routines including migration to cloud-based tools. This position acts as a first line of defense as related to the Enterprise Model Governance policy. This position will primarily interface with model development teams, the MLOps team, and various compliance and oversight functions to ensure that model risk is managed appropriately.
Responsible for creating, maintaining, and updating model management processes for Data Science models that support model management policies
Ensure models are being routinely monitored with metrics published, interpreted, and shared
Ensure appropriate documentation and meta-data are produced from data ingestion, pre-processing, model building to deployment
Ensure operating processes and reviews are established as a timely, efficient, and effective
Continually support the development of new model monitoring processes and updating policies in accordance with GMF audit and model monitoring
Qualifications:
What makes you a dream candidate?
Knowledge of the Data Science lifecycle and steps required to develop, validate, deploy, and monitor models
Knowledge of MLOps highly desirable
Experience with data mining, data querying and knowledge of on-premise (or cloud-based) data management tools
Knowledge of statistical modeling techniques for prediction and classification
Knowledge of Operations Research methodologies for optimization and simulation
Advanced with Microsoft Excel, PowerPoint, and Word
Experience with data analysis and reporting
Understand and build SQL queries in a Data Warehouse environment and data manipulation
Run and understand code built by others for cleaning data and building statistical model in SAS and Python
Ability to work with minimal supervision
Ability to tailor different concepts to various audiences
Proficiency in Power BI development, including report and dashboard creation
Experience in Azure DevOps Agile practice
Working knowledge of Databricks platform
Experience:
Bachelor's degree in Economics, Mathematics, Statistics, Computer Science or other quantitative field; degrees in non-quantitative fields considered with adequate work experience required
Master’s Degree in in Statistics, Economics, Mathematics, Computer Science
0-2 years experience working with and querying large datasets
0-2 years experience with source code management tools like git
0-2 years experience in statistics and Machine Learning Model Governance experience
What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.
Our Culture: Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.
Compensation: Competitive pay and bonus eligibility
Work Life Balance: Flexible hybrid work environment, 2-days a week in office
#LI-hybrid
#LI-MO1
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