Analytics Consultant 5

Job Descriptions:

In this contingent resource assignment, you may: Consult as an expert to develop or influence initiatives and resources for highly complex business and technical needs across Analytics. 
Consult on the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, and advanced analytical and inductive thinking. 
Provide expertise to client senior leadership on innovative Analytics business solutions. 
Strategically engage with client personnel.

Qualifications

Required Qualifications:

7+ years of Analytics experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education..

Project Scope

This contractor will be contributing to the Data Science team which is focused on High-Risk Regulatory Insights and Analytics with solving complex issues across the enterprise. 
Will be Framing business issues, developing hypothesis' on how to solve through data, testing, interpreting solutions, presenting findings, and making recommendations 
This role will be contributing to multiple projects in a highly visible, fast-paced, and collaborative environment

Skills

TOP SKILLS:

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

Soft Skill

Proactive 
Ability to take ownership of tasks 
Core Analytics and problem-solving skills

Intake

Top Skills:

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 
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.