Intern, Data Scientist - Data Science Service Center (DSSC)

Key Skills

AI technology, Data Analysis, Data Analytics, Data Mining, Deep Learning, ETL/ELT technologies, Informatica, OLAP, Python Programming, R Programming, SAS, SQL, SSIS

Job Description

BMW Financial Services NA, LLC was established in 1993, supporting the sales and marketing of BMW products. Subsequently, we have expanded beyond the leasing, retail and commercial financing of a traditional captive-finance company offering a broad variety of products tailored for the BMW, MINI and Rolls-Royce customer. Be a part of our exciting internship program located onsite and in-person at our Columbus, Ohio location. Please note, it is a requirement of this position to work onsite in Columbus, Ohio. Relocation assistance and housing is not available.

We are pleased to offer a 6 Month Internship starting on June 12, 2023, and ending on December 15, 2023 at BMW Financial Services NA, LLC.

Intern, Data Scientist - Data Science Service Center (DSSC)

Do you want to unlock the power of analytics and pave the way to transform our business?

Look no further. BMW Group Financial Services has the Internship Program for you!

Our Data Science Service Center is looking for data experts with serious analytical and statistical skills. You will embrace data analytics tools and methods confidently and responsibly to solve business challenges. You will leverage data to discover patterns and solve strategic analytic business problems and develop static and interactive data visualization of your findings.

Additionally, you will support the development and know-how to transfer for AI and deep learning on key BMW Group projects. You will support analysis of business-critical data and recommend improvements. The intern will work with large data sets within and external to BMW (e.g. internal data, social media data, warranty data, sales, manufacturing etc.) and conduct advanced analytical tasks, such data conversions, ETL, filtering, fusion, aggregations and data mining. Also, you will communicate findings to the Enterprise Data Scientist and business decision makers on latest data analytics technologies and assist the team in process matters as related to development/support.

If you know how to combine large amounts of data in a meaningful way to gain business insights and if you can design and build predictive and prescriptive models using statistical modeling, machine learning and optimization, then apply now!

We offer a flexible schedule. A great opportunity to gain broad experience in analyzing financial services data. We partner you with senior leadership to develop, maintain and improve existing strategies.

This program will run from June 12, 2023 - December 15, 2023.

Our culture and values make BMW Financial Services NA, LLC the ultimate working environment. Our core values are 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? Jump into the driver's seat and apply for this exciting Internship opportunity with BMW Financial Services today!

Qualification:

Qualifications and Experience Required:

• Currently enrolled full time as a 3rd or 4th year student in an undergraduate program or enrolled in a graduate program at an accredited college or university through at least December 2023.
• Ability to develop from complex data analysis web based solutions for business use in understanding data.
• Strong understanding of data warehousing architectural approaches.
• Knowledge of data warehouse and business intelligence tools and technologies such as Informatica, SSIS, Business Objects, SAS, OLAP, etc.
• Programming: Python and/or R and/or SQL.
• Legally permitted to work in the United States.
• Complete and pass a substance abuse test.
• It is required to work onsite and in-person at our Columbus, Ohio office. Relocation and housing assistance is not provided.
• The ability to work 40 hours per week between the core hours of 8:00AM EST and 6:00PM EST

Preferences:

• Major in Statistics, Data Analytics, Computer Science and/or Engineering.
• Enrolled in a graduate program at an accredited college or university.