Data Scientist II (ADBL175)

Amazon • Newark, NJ

1d • Remote

About The Position

Independently own, design, and implement scalable and reliable solutions
to support or automate decision making throughout the business. Apply a range of
data science techniques and tools combined with subject matter expertise to
solve difficult business problems and cases in which the approach is unclear.
Acquire data by building the necessary SQL/ETL queries. Import processes through
various company specific interfaces for accessing RedShift, and S3/edX storage
systems. Deliver artifacts on medium size projects that affect important
business decisions. Build relationships with stakeholders and counterparts, and
communicate model outputs, observations, and key performance indicators (KPIs)
to the management to develop sustainable and consumable products and product
features. Explore and analyze data by inspecting univariate distributions and
multivariate interactions, constructing appropriate transformations, and
tracking down the source and meaning of anomalies. Build production-ready models
using statistical modeling, mathematical modeling, econometric modeling, machine
learning algorithms, network modeling, social network modeling, natural language
processing, large language models and/or genetic algorithms. Validate models
against alternative approaches, expected and observed outcome, and other
business defined key performance indicators. Implement models that comply with
evaluations of the computational demands, accuracy, and reliability of the
relevant ETL processes at various stages of production. Position reports to
Newark, NJ office; however, telecommuting from a home office may be allowed.

Requirements

• Requires a Master’s degree in Statistics, Computer Science, Computer Engineering, Data Science, Machine Learning, Applied Math, Operations Research, or a related field plus two (2) years of experience as a Data Scientist or other occupation involving data processing and predictive Machine Learning modeling at scale.
• Two (2) years in each of the following: - Utilizing specialized modelling software including Python or R - Building statistical models and machine learning models using large datasets from multiple resources - Building non-linear models including Neural Nets, Deep Learning, or Gradient Boosting.
• One (1) year in each of the following: - Building production-ready solutions or applications relying on Large Language Models (LLM), accessed programmatically and beyond just prompting - Evaluating LLM results at scale or fine-tuning LLMs - Building production-ready recommendation systems - Using database technologies including SQL or ETL.
• Alternatively, will accept a Bachelor’s degree and five (5) years of experience.

Nice To Haves

• Please see job description and the position requirements above.

Responsibilities

• Independently own, design, and implement scalable and reliable solutions to support or automate decision making throughout the business.
• Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the approach is unclear.
• Acquire data by building the necessary SQL/ETL queries.
• Import processes through various company specific interfaces for accessing RedShift, and S3/edX storage systems.
• Deliver artifacts on medium size projects that affect important business decisions.
• Build relationships with stakeholders and counterparts, and communicate model outputs, observations, and key performance indicators (KPIs) to the management to develop sustainable and consumable products and product features.
• Explore and analyze data by inspecting univariate distributions and multivariate interactions, constructing appropriate transformations, and tracking down the source and meaning of anomalies.
• Build production-ready models using statistical modeling, mathematical modeling, econometric modeling, machine learning algorithms, network modeling, social network modeling, natural language processing, large language models and/or genetic algorithms.
• Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators.
• Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• paid time off
• parental leave

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level