Sr Quantitative Analyst - Pricing

Why Quantitative Pricing at GM Financial?

The Sr Quantitative Analyst - Pricing plays a key role in enhancing pricing strategies and processes through pricing model development and data driven business solutions. The Associate will focus on improving model integrity and accuracy through the collection, analysis, interpretation, and presentation of origination and forecast data. They will also apply advanced quantitative and analytical skills to improve decisions supporting various internal clients. This position will interact with many other departments to achieve overall company objectives.

Experience ----------------

• 2-4 years of related work experience or similar quantitative field
• Greater than 5 years of modeling experience and strong coding skills

Education ------------

• Bachelor's Degree
• Master's Degree or PhD in Statistics, Applied Mathematics, Econometrics, Operations Research, Engineering, Computer Science or similar quantitative field

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
• 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
• Bonus eligibility

Work Life Balance -----------------

• Flexible hybrid work environment
• 2-days a week in office

About the Role ----------------

The Sr Quantitative Analyst - Pricing will be responsible for:

• Developing and maintaining complex pricing models and performing profitability analysis for all of International Operations
• Monitoring and validating model performance and updating models as needed
• Developing and maintaining various databases, technical models, and reports required to support product and pricing proposals and analytic responsibilities
• Conducting ad hoc projects incorporating project design, data collection, model development, and analysis
• Summarizing findings and presenting results
• Developing recommendations for pricing policies and procedures
• Gathering and analyzing data to determine impact to company profitability and financials
• Providing direction, training, and guidance to less experienced pricing and finance personnel and leading projects or special assignments as required

What Makes You an Ideal Candidate? -----------------------------------

• Strong quantitative, analytical, and data mining skills
• Ability to identify and understand business issues and map these issues into quantitative questions
• Efficient modeling skills with very large datasets using SAS, SQL, Python, or R
• Proficiency in statistical experimental design or econometrics
• Ability to design and implement model documentation and monitoring protocols
• Demonstrated understanding and experience with technical systems, rational datasets, data warehouses, data mining, and data analysis techniques
• Advanced knowledge of principles, standards, practices, and techniques relating to profitability modeling for a financial firm
• Knowledge of applied statistical methodologies including multiple regression, logistic regression, sampling methodologies, time series, survival analysis, cluster analysis, categorical data analysis, decisions trees, multivariate methodologies, Bayes networks, non-parametric techniques, principal components, and linear programming techniques
• Effective written and verbal presentation skills with an ability to communicate well with Senior Management
• Organized, detail-oriented, and ability to work independently with minimum instruction or supervision
• An ability to interact collaboratively with internal customers and external vendors
• Capable of managing multiple and varied projects including the ability to coordinate and balance numerous tasks in a time-sensitive environment, under pressure, and meeting deadlines
• Demonstrated quantitative skills and ability to apply complex financial and mathematical principles
• Advanced process and model documentation skills
• Advanced Excel, SQL, Python, R, and/or SAS software skills
• Good Word and Power Point skills