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Technical Risk Analysts Specialist II

Charlotte, North Carolina;

Job Description:

Enterprise Risk Analytics develops and maintains a portfolio of models used by the bank’s automated anti-money laundering detection and monitoring platforms. The team performs annual performance assessments on other analytical tools and systems used by teams across Global Financial Crimes Compliance.  For this position the associate will be responsible for sourcing, integrating, cleansing and validating structured and unstructured data from large diverse data sources.  The associate will execute feature engineering in support of model development and support model documentation and model deployment activities. 

The candidate will have the opportunity to learn the latest developments in AML/Economic Sanctions, interact with industry-leading subject matter experts, apply an extensive set of data analytics/data science methods to meet business and regulatory requirements, and develop a career in this fast-paced and ever-changing world. This role demands a highly diverse skillset, including quantitative, analytical, organizational, communication, and technical capabilities

As a Risk Analysis Specialist II your main responsibilities will involve:

  • Perform in-depth data analysis on diverse large data using a variety quantitative tools

  • Provide holistic data assessment using basic statistics, data artifacts, ad-hoc analysis and data visualization

  • Provide written and verbal communication to quantitative, technical and business stakeholders

  • Identify and recommend improvements to data analytics, data quality and feature engineering

Position Overview

Responsible for independently conducting data analysis in support of model development projects. Assist other Quantitative Financial Analysts (QFA) to source, integrate, validate and engineer data for model development. Responsible for documentation for all data activities.  Work with Technology staff in design systems that consistently process and prepare data for model execution.

Required Skills

  • Experience programming skills in both SQL and Python

  • Professional experience wrangling large datasets

  • Experience with Hadoop and Teradata systems

  • Knowledge of basic statistics, data analytics, feature engineering, data visualization and quality assurance

  • Strong technical writing, communication, and presentation skills

  • Ability to multitask and work under pressure to meet timelines

  • Undergraduate STEM degree withy 2+ years of experience working in data analytics/science or a Masters STEM degree

Desired Skills:

  • Understanding of current modeling and data science principals including but not limited to time-series analysis, machine learning, and deep learning

  • Experience with the entire software development lifecycle (SDLC) including maintaining and improving existing codebases and peer review changes

  • Ability to effectively communicate technical/quantitative topics to non-technical audiences

  • Professional experience with the software /tools including: Tableau, JIRA, Bitbucket, Confluence, LaTex

  • Good applied statistics skills, such as distributions, statistical testing, feature engineering

  • Understanding of machine learning techniques able to demonstrate basic understanding of algorithms

Job Band:

H5

Shift: 

1st shift (United States of America)

Hours Per Week:

40

Weekly Schedule:

Referral Bonus Amount:

0

Job Description:

Enterprise Risk Analytics develops and maintains a portfolio of models used by the bank’s automated anti-money laundering detection and monitoring platforms. The team performs annual performance assessments on other analytical tools and systems used by teams across Global Financial Crimes Compliance.  For this position the associate will be responsible for sourcing, integrating, cleansing and validating structured and unstructured data from large diverse data sources.  The associate will execute feature engineering in support of model development and support model documentation and model deployment activities. 

The candidate will have the opportunity to learn the latest developments in AML/Economic Sanctions, interact with industry-leading subject matter experts, apply an extensive set of data analytics/data science methods to meet business and regulatory requirements, and develop a career in this fast-paced and ever-changing world. This role demands a highly diverse skillset, including quantitative, analytical, organizational, communication, and technical capabilities

As a Risk Analysis Specialist II your main responsibilities will involve:

  • Perform in-depth data analysis on diverse large data using a variety quantitative tools

  • Provide holistic data assessment using basic statistics, data artifacts, ad-hoc analysis and data visualization

  • Provide written and verbal communication to quantitative, technical and business stakeholders

  • Identify and recommend improvements to data analytics, data quality and feature engineering

Position Overview

Responsible for independently conducting data analysis in support of model development projects. Assist other Quantitative Financial Analysts (QFA) to source, integrate, validate and engineer data for model development. Responsible for documentation for all data activities.  Work with Technology staff in design systems that consistently process and prepare data for model execution.

Required Skills

  • Experience programming skills in both SQL and Python

  • Professional experience wrangling large datasets

  • Experience with Hadoop and Teradata systems

  • Knowledge of basic statistics, data analytics, feature engineering, data visualization and quality assurance

  • Strong technical writing, communication, and presentation skills

  • Ability to multitask and work under pressure to meet timelines

  • Undergraduate STEM degree withy 2+ years of experience working in data analytics/science or a Masters STEM degree

Desired Skills:

  • Understanding of current modeling and data science principals including but not limited to time-series analysis, machine learning, and deep learning

  • Experience with the entire software development lifecycle (SDLC) including maintaining and improving existing codebases and peer review changes

  • Ability to effectively communicate technical/quantitative topics to non-technical audiences

  • Professional experience with the software /tools including: Tableau, JIRA, Bitbucket, Confluence, LaTex

  • Good applied statistics skills, such as distributions, statistical testing, feature engineering

  • Understanding of machine learning techniques able to demonstrate basic understanding of algorithms

Shift:

1st shift (United States of America)

Hours Per Week: 

40

Learn more about this role

Full time

JR-21039409

Band: H5

Manages People: No

Travel: No

Manager:

Talent Acquisition Contact:

Jillian Teeter

Referral Bonus:

0