Junior Data Scientist (Remote, W2 Or 1099 Candidates Only))

Junior Data Scientist (Remote,W2 or 1099 candidates only)

100% Remote,

The Opportunity

As a leader in digital financial services, our customer and employee experiences run on data. We depend on the Ally analytics community to fuel these journeys and to help nearly 10,000 leaders and employees make countless data-driven decisions every day. Every individual is a risk manager. In alignment with our risk culture, this position will ensure the appropriate identification, assessment, and measurement of risk related to the Consumer Auto portfolio. When necessary, identified risks will be escalated to the appropriate channels to ensure reasonable resolution.

We're looking for a passionate Junior Data Scientist with great technical skills for our Auto Consumer Asset Management group. This person will report to the Director of Data Science for consumer asset management, with responsibilities of (1) supporting through-the-cycle predictive analytics for collection strategy & consumer risk (2) applying data science techniques (Decision Trees, Clustering etc.) to identify key drivers of customer payment behavior and optimize collection treatment for delinquency (3) processing and analyzing massive external data (e.g. credit bureau, data vendors) to support ML/Risk Modeling solutions for account management optimization. The ideal candidate should be passionate about data science and consumer risk analytics for banking & financial services. Strong Snowflake SQL and Python programming skill is a must. Do you have a focus on predicting customer behavior, managing portfolio risk, strong analytical skills, and a desire to make an impact? If you are a creative and critical thinker, storyteller, learner, and innovator and want to work in an environment focused on using data science and big data tech, keep reading.

The Job Itself:

This role is quantitative in nature and requires the individual highly capable of interrogating and analyzing massive account-level data using Snowflake SQL, Python. Skills for other programming, data mining tools such as SAS, R are preferred. He or she will join the data science team under consumer asset management of auto finance business, with the responsibility to support collection strategy optimization and predictive analytics for consumer risk management. Daily work involves all phases of data science projects, including account-level data processing and validation, exploratory analysis for hypothesis testing and variable screening, communication and presentation to executive leadership team. This senior data scientist must be an innovative and strategic thinker, willing to challenge status quo, can learn quickly, is self-motivated and detail oriented.

Key Responsibilities include:

• Support complex business optimization projects via predictive analytics (e.g., customer segmentation, clustering) for auto finance asset portfolio management; Independently prepare and analyze large, account-level consumer data from internal and external sources to identify customer behavior and strong risk indicators for auto finance consumer.
• Understanding of risk management concepts and key performance drivers within consumer lending portfolios; Perform ad-hoc analysis, prepare crisp summary, and deliver recommendation.
• Support the implementation of collection treatment optimization solution (what delinquent customers should receive which collection treatments by when).
• Ability to think strategically, use sound judgement, and balance short and long-term risk decisions; Strong communication and collaboration skills; ability to work effectively across multiple team.

The Skills You Bring

• Master's degree in a quantitative field.
• 3-5 years financial risk analytics, data science and/or predictive modeling work experience
• Good knowledge of statistics and data mining (e.g., Correlation, Regression, Decision Tree segmentation), and programming skills with exploratory data analysis using Python. Knowledge of R or SAS are preferred.
• Minimum 3 years of hands-on experience working with large, consumer account-level datasets using SQL (ideally Snowflake) and Python programming.
• Bachelor’s Degree Preferred in Quantitative/Technical Discipline (Mathematics, Computer Science, Data Science/Analytics, Economics).

All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.