Sr Associate, Data Science - Credit and Lending Modeling

Sr Associate, Data Science - Credit and Lending Modeling

Country: United States of America

Who We Are
The Models and Data Science team within the Data and Analytics Center of Excellence is focused on applying data science (from fine-tuned linear models through to machine learning) to our petabytes of data to uncover insights about our customers and their financial behaviors, assess risk and lending opportunities, drive scalable growth, and improve the digital banking experience.

Our data scientists work with key business leaders and decision makers to refine and solve problems by mining, analyzing, and modeling data to provide insights that drive change. The day-to-day includes exploratory analysis to understand data structures and relationships, working closely with our business partners to build insight into new problems, research to refine a methodology, cranking out lightning-fast machine learning code to create a model that predicts trends and automates validation, collaborating with cross-functional teams, or visualizing and sharing their results with executives. Our work as innovators means that we are approaching new problems on novel (and potentially unstable) data and there is no playbook for best practice; instead, we rely on our understanding of applied statistics and incrementality, alongside industry knowledge of trends in customer lending behavior and a toolbox of machine learning approaches/algorithms to resolve the tension between complexity, scope, and explainability.

The ideal data scientist on the MDS squad is comfortable working with a variety of partners (business verticals, IT, data engineering, risk...etc.) and data (structured, unstructured, streaming) in a shared code repository utilizing multiple programming languages and frameworks to deliver state-of-the-art analytics and models in an agile environment.

We are from a range of backgrounds - mathematicians, statisticians, economists, engineers, computer scientists, financiers, and of course data scientists – but we are all skilled in research methods, and are obsessed with our customers, financial projections, data science, research, AI, programming, clean and powerful data visualizations to communicate our ideas, and collaborating to find the best approach to emerging questions.

Who You Are
We are looking for a senior quant with extensive experience in Data Science, Credit Risk or Consumer Lending to join our first line model team as we expand our suite of credit models (both PL and CC).

You:

·        Have a proven record (in academia or industry) of development on credit models covered by regulation. Within the guardrails of compliance, documentation, and model operations you still manage to be creative and tackle difficult questions with fresh ideas

·        Explain your logical and structured thinking/processes in different ways to different people while maintaining the honesty and integrity of your analysis

·        Have a passion for clear communication and have built some stunning charts and visualizations in the past which told a very important story

·        Love being part of a fast-moving team and welcome feedback to learn

·        Are organized and able to document what you produce and create frameworks to monitor model performance

·        Are not afraid to ask questions and seek answers in a self-determined manner

·        Are comfortable with ambiguity and charting a path through quantitative analysis

·        Are committed to making the world a better place and can adhere to our corporate culture and values.

Examples of potential work
Much of the work will be acting as an internal consultant within the broader analytics center of excellence, engaging in a range of projects for various departments throughout the bank. This could include, for example, creating proof of concept work on unstructured data, working to understand customer behavior and key drivers of customer satisfaction in real-time, or aiming to answer questions that are difficult to define and measure. One day you might be fitting distributions to historical data and modelling extreme future events, the next helping colleagues find anomalies in their data indicative of maleficent intent. Through it all, you will draw upon your well-stocked toolkit of mathematical understanding and coding skills, and an openness to collaborate to create new methodologies.
Role And Responsibilities
 

·        Create, implement, and validate Scorecards and machine learning models including rigorous documentation of code and results

·        Investigate, define, and iterate with business partners to define business problems and data science use cases

·        Develop new approaches as needed to quantify emerging risks and opportunities

·        Communicate in person, via email, over teleconference, and in virtual meetings with internal and external team members

·        Mine and manipulate data from disparate systems and environments

·        Use statistics to analyze data and produce insights on tight timelines

·        Work as part of a team and collaborate across groups

·        Problem solve on varied and concurrent projects, self-organize your work and projects (with input on prioritizing from team leader)

·        Present materials (visual, verbal) to relevant parties about data science concepts, data architectures, and model results

·        A desire to share findings, methodologies, etc. and contribute to the literature through internal white papers and peer reviewed publications.

Technical Skills
 

·        6 years of credit risk experience in methodology development, or validation

·        9+ years of experience in a quantitative field: data mining/advanced analytics applied to large-scale data-intensive projects

·        Honed application of the research process – exploration, hypothesis creation, and iteration

·        Deep understanding of statistics or advanced mathematics like Bayesian inference, optimization, linear algebra

·        Ability to explain failures as well as successes as you build understanding in an emerging area

·        Confidence with cloud computing

·        Advanced in at least one machine learning programming language and framework (R, Python,...)

·        Experience using data science methodologies including regression/classification, time-series modelling, algorithm/network optimization, NLP, (Convolutional) Neural Nets/AI

·        Appreciation for the interconnected nature of customer behavior and familiarity in applying techniques from computational graph theory (Neo4j...)

·        Awareness of model bias and how to mitigate it

·        Master's or research degree in a quantitative discipline

Primary Location: Boston, Ma (Hybrid)

Other Locations Considered: New York City, NY; Miami, FL; Dallas, Tx

Organization: Santander Bank, N.A.

EEO Statement:  At Santander, we value and respect differences in our workforce.  We actively encourage everyone to apply.   

Santander is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, genetics, disability, age, veteran status or any other characteristic protected by law.

Working Conditions: Frequent Minimal physical effort such as sitting, standing and walking. Occasional moving and lifting equipment and furniture is required to support onsite and offsite meeting setup and teardown. Physically capable of lifting up to fifty pounds, able to bend, kneel, climb ladders.
Employer Rights: Employer Rights:This job description does not list all of the job duties of the job. You may be asked by your supervisors or managers to perform other duties. You may be evaluated in part based upon your performance of the tasks listed in this job description. The employer has the right to revise this job description at any time. This job description is not a contract for employment and either you or the employer may terminate at any time for any reason.

$112,500.00 USD

$195,000.00 USD