Principal Associate, Data Scientist – Generative AI Systems

Jobtailor; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor in New York, NY is seeking a data scientist/ML engineer to build and deploy machine learning models and generative AI solutions. You will collaborate with data scientists, engineers, and product managers to transform complex analytics into business impact.

The role requires strong experience in Python, SQL, and ML, plus cloud experience with AWS. You will work on customer-facing applications and contribute to cutting-edge NLP/AI research.

Qualifications

• Bachelor's degree in a quantitative field plus 5 years of experience performing data analytics, or Master's degree in a quantitative field/MBA with quantitative concentration plus 3 years of experience, or PhD in a quantitative field
• Quantitative fields include Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related quantitative fields
• At least 1 year of experience working with AWS
• At least 3 years of experience in Python, Scala, or R
• At least 3 years of experience with machine learning
• At least 3 years of experience with SQL
• Experience with statistical modeling, validation, backtesting, clustering, classification, sentiment analysis, time series, deep learning, and big data
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
• Capital One will consider sponsoring a new qualified applicant for employment authorization

Responsibilities

• Partner with cross-functional data scientists, software engineers, and product managers to deliver customer-focused products
• Leverage Python, Conda, AWS, H2O, Spark, and other technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Translate complex data science work into tangible business goals
• Develop generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing
• Deliver internal and customer-facing applications with product, technology, and design teams
• Experiment with emerging generative AI technologies and contribute research to NLP and AI/ML conferences

Skills

Machine Learning

Python Programming

SQL

Statistical Modeling

Data Analytics

Deep Learning

Clustering

Classification

Time Series Analysis

Big Data

Education

Bachelor's degree in a quantitative field

Master's degree in a quantitative field/MBA with quantitative concentration

PhD in a quantitative field

Tools

AWS

H2O

Spark

Conda

Open-Source Tools

Job description

• Partner with cross-functional data scientists, software engineers, and product managers to deliver customer-focused products
• Leverage Python, Conda, AWS, H2O, Spark, and other technologies to analyze large volumes of numeric and textual data
• Build machine learning models through design, training, evaluation, validation, and implementation
• Translate complex data science work into tangible business goals
• Develop generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing, and time-series sequencing
• Deliver internal and customer-facing applications with product, technology, and design teams
• Experiment with emerging generative AI technologies and contribute research to NLP and AI/ML conferences

Requirements

• Currently has, or is in the process of obtaining, a required degree expected to be obtained by the scheduled start date
• Bachelor's degree in a quantitative field plus 5 years of experience performing data analytics, or Master's degree in a quantitative field/MBA with quantitative concentration plus 3 years of experience, or PhD in a quantitative field
• Quantitative fields include Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related quantitative fields
• At least 1 year of experience working with AWS
• At least 3 years of experience in Python, Scala, or R
• At least 3 years of experience with machine learning
• At least 3 years of experience with SQL
• Experience with statistical modeling, validation, backtesting, clustering, classification, sentiment analysis, time series, deep learning, and big data
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms
• Capital One will consider sponsoring a new qualified applicant for employment authorization

Core Competencies

Demonstrates expertise in developing machine learning models and generative AI solutions, leveraging Python, AWS, and statistical analysis to drive data-driven business outcomes. Proven ability to collaborate with cross-functional teams to deliver impactful customer-focused products.

Highest-signal resume keywords

• Machine Learning
• Python Programming
• AWS Experience
• Data Analytics
• Statistical Modeling

Hard Skills

• Machine Learning
• Python Programming
• SQL
• Statistical Modeling
• Data Analytics
• Deep Learning
• Clustering
• Classification
• Time Series Analysis
• Big Data

Industry Keywords

• Data Science
• Quantitative Analysis
• Natural Language Processing
• Generative AI
• Data Engineering

Tools & Technologies

• AWS
• H2O
• Spark
• Conda
• Open-Source Tools