Lead Quantitative Analytics Associate

Jobtailor

New York (NY)

On-site

USD 110,000 - 160,000

Full time

14 days+

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Job summary

Jobtailor in New York is seeking a quantitative analyst to conduct in-depth data analysis, develop models, and translate findings into actionable business insights.

The role requires advanced skills in statistics, machine learning, and data engineering, with experience in SQL/NoSQL, Python or R, and cloud-based computing. You will collaborate with business partners to address banking operations and risk management needs.

Qualifications

Bachelor’s degree (or equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or another quantitative discipline
Minimum of 2 years of relevant experience, or minimum of 1 year of experience with a Master’s or PhD
Understanding of data structures and transformations
Ability to identify and capture information needed for business needs or analysis
Knowledge of data controls, hypothesis testing, and root-cause analysis
Advanced Microsoft Office Suite skills
SQL/NoSQL knowledge
Knowledge of relational data structures
Experience selecting and retrieving structured and unstructured data, including archival and ETL
Database knowledge
Advanced Python, R, or SAS skills
Efficient coding and strong code controls
Ability to translate code into high-level commentary
Understanding of cloud-based and distributed computing
Understanding of model use, requirements, implementation needs, and Model Risk Management foundations
Ability to test for model deterioration and model health
Understanding of machine-learning fundamentals and statistical measurements used in modeling frameworks
Ability to produce and identify information through statistical analysis
Ability to explain model insights to peers and the analytics community
Ability to identify the preferred approach for a problem statement
Solid writing and presentation skills
Understanding of business partner strategy and banking operations
Ability to analyze and recommend solutions to moderately complex problems

Responsibilities

Conduct quantitative analysis, including hypothesis testing and root-cause analysis, on large datasets with increasing autonomy
Identify information needed for analysis and business questions
Create data structures and transformations for group analysis
Develop, maintain, and anticipate implementation considerations for statistical and machine-learning models
Ensure models address the appropriate business need
Select the appropriate analytical approach for each problem statement
Anticipate business needs and continuously improve models and processes
Translate data into insights and communicate findings to peers and the analytics community
Support working groups and collaborate with business partners

Skills

Quantitative Analysis

Statistical Modeling

Machine Learning

Hypothesis Testing

Root-Cause Analysis

Education

Bachelor’s degree in quantitative field

Master’s or PhD preferred

Tools

Python

SAS

SQL/NoSQL

ETL

Cloud Computing

Distributed Computing

Job description

Conduct quantitative analysis, including hypothesis testing and root-cause analysis, on large datasets with increasing autonomy
Identify information needed for analysis and business questions
Create data structures and transformations for group analysis
Develop, maintain, and anticipate implementation considerations for statistical and machine-learning models
Ensure models address the appropriate business need
Select the appropriate analytical approach for each problem statement
Anticipate business needs and continuously improve models and processes
Translate data into insights and communicate findings to peers and the analytics community
Support working groups and collaborate with business partners

Requirements

Bachelor’s degree (or equivalent) in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or another quantitative discipline
Minimum of 2 years of relevant experience, or minimum of 1 year of experience with a Master’s or PhD
Understanding of data structures and transformations
Ability to identify and capture information needed for business needs or analysis
Knowledge of data controls, hypothesis testing, and root-cause analysis
Advanced Microsoft Office Suite skills
SQL/NoSQL knowledge
Knowledge of relational data structures
Experience selecting and retrieving structured and unstructured data, including archival and ETL
Database knowledge
Advanced Python, R, or SAS skills
Efficient coding and strong code controls
Ability to translate code into high-level commentary
Understanding of cloud-based and distributed computing
Understanding of model use, requirements, implementation needs, and Model Risk Management foundations
Ability to test for model deterioration and model health
Understanding of machine-learning fundamentals and statistical measurements used in modeling frameworks
Ability to produce and identify information through statistical analysis
Ability to explain model insights to peers and the analytics community```
Ability to identify the preferred approach for a problem statement
Solid writing and presentation skills
Understanding of business partner strategy and banking operations
Ability to analyze and recommend solutions to moderately complex problems

Core Competencies

Demonstrates expertise in quantitative analysis, including hypothesis testing and root-cause analysis, while effectively translating data insights for business applications. Proficient in statistical and machine-learning model development, with a strong understanding of data structures and transformations.

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