Principal Data Scientist

Brief Role Description

This position is Career Level 30P Home Based with a Role Classification of Fully Remote.

Salary range is dependent on factors such as geographical differentials, industry-based experience, skills, training, credentials, and other qualifications.

In the state of California, the salary range is $131,600 - $224,100.
In the state of Colorado, the salary range is $119,600 - $203,700.
In the state of Washington, the salary range is $131,600 - $224,100.
In New York City, New York, the salary range is $143,500 - $244,400.
In Westchester County, New York, the salary range is $143,500 - $244,400.

Benefits for this position include:

Eligibility for annual performance bonus
Healthcare benefits
401(k), with company match
Defined contribution retirement program
Tuition reimbursement
Company lease car program
Paid time off

Role Summary

The role resides within VWFS’s Data Science & AI CoE team and focuses on end-to-end model development. It requires a proven track record of successful model development and quantifiable business impact. It is not primarily a data analytics or ML engineering role. 

The Principal Data Scientist will lead high-impact initiatives that directly contribute to VWFS’s stated goal to become a data and AI-driven organization. Potential projects cover the entire spectrum of automotive finance, from automated decision-making to fraud detection and business process improvement.

Responsibilities within this Role

•    Lead data science product development, set standards, best practices, and innovation for the data science CoE (25%)
•    Experimentation, build, integration of data science solutions into core business processes and new opportunities (75%)
Responsibilities will include:

•    Definition and ongoing improvement of a machine learning environment 
•    Develop and deploy AI models that impact business decisions 
•    Establish best practices and governance routines to ensure adherence to model management policies, peer reviews, and compliance to our policy standards for privacy, ethics, and bias.
•    Bring relevant data science techniques, algorithms, and tools to your team 
•    Provide technical oversight, help and mentorship to the junior data scientists on the team 
•    Apply suitable techniques for model testing and tuning, to assess accuracy, fit, validity, and robustness
•    Innovate new ML methods in the data science space and drive change throughout the business 
•    Contributes to code documentation, maintains playbooks, and provides timely progress updates
•    Help generate compelling hypotheses to drive new business creation

Qualification requirements

Required Education:

•    Bachelor’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field
•    Master’s degree in Computer Science, Statistics, Economics, Engineering, Operations Research or similar quantitative field

Relevant Experience:

•    12+ years of data & analytics work experience with 8+ years in data science
•    7+ years in utilizing methods and tools to extract, curate, explore, and analyze data from large data sources
•    7+ years in developing, integrating and deploying machine learning solutions into the business decision making process
•    7+ years in leveraging algorithms, tune parameters and back testing validation
•    5+ years leading ML project development

Skills:

•    Collaborate with product owners and product managers to translate business requirements into impactful AI solutions that scale
•    Build, integrate and deploy machine learning solutions into the business decision-making process
•    Thorough knowledge of machine learning models, including both traditional ML and GenAI
•    Utilize a consultative approach to work with the business to solve challenging problems using various analytical techniques
•    Embrace, research, explore, and enable new quantitative techniques and technologies in data science that will help define VWFS as an industry leader in the application of data science techniques

•    Extensive experience with model evaluation and solid grasp of A/B testing and causal analysis
•    Research new data sources and analytical tools, contribute to new application development, and data quality improvement efforts
•    Ability to originate curiosity to collaborate with different business units to co-create solutions
•    Passion for data analysis and problem solving
•    Establishes and maintains effective performance tracking; identifies improvement opportunity, form hypothesis, propose, design and implement tests to drive strategy enhancement and optimization.
•    Superior ability to communicate technical ideas and results to non-technical users in written and verbal form

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