Strategic RiskWoodcliff Lake, New Jersey09.11.2021
Lead Data Scientist - Strategic Risk (Hybrid)
BMW Group Financial Services NA, LLC is one of the 26 worldwide subsidiaries of the Financial Services Division of BMW AG. Our momentum is moving at such a rapid pace that we continually exceed average international growth rates and we constantly create new opportunities for our employees worldwide. Be a part of our exciting growth by expressing an interest in our Lead Data Scientist - Strategic Risk position located at our Woodcliff Lake, NJ office. This position is hybrid between office and at home work. (Note: Due to having to work some in the office, living in the Woodcliff Lake area or surrounding vicinity would be required.)
As the Lead Data Scientist - Strategic Risk, you are responsible for data discovery and building predictive, prescriptive models utilizing machine learning algorithms supported by strong statistical theory. The problems will typically be identified by a business unit, and at times, will be formulated by you. In addition, you will use a variety of data mining/data analysis methods, data tools, building and implementing models, using/creating algorithms, standard statistical techniques, and creating/running simulations, while adhering to Model Development Life Cycle (MDLC) and internal standards for model development. You will present results in an easy to comprehend way for non-technical stakeholder audiences.
You will mentor other Data Science, Data Analysts, and Business Intelligence Analysts across the department as well as collaborate with a broad cross functional team including the Enterprise Data Scientist, and the rest of the data and analytical community across the organization. In addition, you will also be responsible for choosing and standardizing the department's use of tools, packages, and processing frameworks to solve business problems.
As the Lead, you will be the primary point of contact for Model Owners and Validator and will be responsible for managing projects by planning out the timelines, defining deliverables, ensuring timely completion and communication with stakeholders. You will develop in-depth knowledge of the new and used car performance with regards to lifecycle, age, cost of retail, mileage as well as many other factors impacting the values of new and used cars; acquire comprehensive understanding of customer behavior driving certain decisions such as customer purchases and early terminations; foster general understanding of quantitative techniques amongst business partners and the Executive Team; enforce and practice Model Risk Management activities as defined in the Model Risk Governance Policy. You will also serve as point of contact for model related inquiries from quantitative auditors and regulators.
Join the BMW Financial Services team and enjoy a high-performance benefits package which includes:
Company paid medical, dental and vision insurance
Retirement Income Account (RIA)
Employee car program
401(k) savings plan
Even more so than the generous compensation and benefits, the culture and values of BMW Financial Services make it the ultimate working environment. These values include such things as, Responsibility, Appreciation, Transparency, Trust, and Openness. We allow these values to guide the way we conduct ourselves and our business.
What are you waiting for? Put yourself in the driver's seat of your career and apply for our Lead Data Scientist - Strategic Risk position today!
Requirements : Minimum of 5 years of professional experience in a corporate environment; to include each of the following (3 years with a post-graduate degree):
Report and dashboard development using BI toolsSQL, Data Preparation, Data Science predictive model developmentExperience in building and deploying Statistical and Machine Learning (ML) solutions using various supervised/unsupervised ML algorithms (Examples: Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc.)Data exploration and mining 2 year of coaching and technical leadership Advanced understanding of the quantitative and statistical methods and theory supporting the Data Science and ML solutionsExperience communicating Data Science techniques to non-technical audiences.
B.A./B.S. degree in Statistics, Mathematics, Computer Science, Economics, or similar quantitative field. (Post-Graduate degree may account for 2 years of Data Science experience.)
PreferencesFinancial Services or Automotive Industry experience Understanding of data warehouse architecture and design; star schema, Kimball-based solutions Experience with AWS