Job Details
Strong skills in – SAS, SQL, and/or Python
Strong Background in statistical modeling and data engineering
Communications – Ability to present findings, flag potential issues, and collaborate with team/ leadership consistently
7 years of professional experience
5 years of modeling experience
Statistical modeling AND data engineering background
SAS and/or Python, SQL is typically embedded with those.
Good communicator with a strong work ethic
Soft Skill:
Proactive
Ability to take ownership of tasks
Core Analytics and problem-solving skills
Additional Skills:
This team has a variety of initiatives they re focused on when making models based around Escalations calls.
One is Customer Fairness, where Legal guidelines could be adjusted to be more customer friendly to improve the customer experience.
Some projects are straight forward where a question comes to light and they look through text analysis for other instances of that issue.
Other projects involve building models to provide a safety net around policy and procedure, like building a model to identify if disclosures are being stated in the calls and flag who may need additional training if they’re not.
Team has also built models that identify when payments don t meet a typical pattern so that client can be followed with for clarification.
Work is assigned, will have independence in their methods for delivering.
Some tasks may be data engineering, some may be modeling, some may be emergency deliverables or short term and last a couple days, others could last months.
Some projects may be executed individually but peer checked, others may be collaborative.
Team is based in SAS but is open to having someone based in Python.
Needs to be able to not only statistically model, but do the data engineering where they prepare the data to be analyzed.
Key thing missing from this team s background is someone with a core modeling background, is a bit too slanted toward the data engineering.
Financial industry experience is preferred, but other industries like insurance have a lot of overlap.
Should have systematic quantitative education of some sort (economics, psychology, mathematics, etc) as well as established experience in developing and executing models.
