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Remote Amazon Data Science Jobs in Connecticut (NOW HIRING)

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Remote Amazon Data Science information

What is the difference between Remote Amazon Data Science vs Remote Amazon Data Analyst?

AspectRemote Amazon Data ScienceRemote Amazon Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/R; experience with machine learningBachelor's in Data Analysis, Business, or related fields; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, cross-functional projects, remote data science platformsRemote reporting, data interpretation, and visualization tasks within Amazon teams
Employer & Industry UsageAmazon's data science teams focusing on predictive modeling, ML, and AIAmazon's data analysis teams focusing on reporting, dashboards, and business insights

Remote Amazon Data Science involves developing machine learning models and advanced analytics, requiring programming and statistical skills. In contrast, Remote Amazon Data Analyst roles focus on interpreting data, creating reports, and supporting decision-making with less emphasis on coding. Both roles are integral to Amazon's data-driven strategies but differ in technical complexity and daily tasks.

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The most popular types of Amazon Data Science jobs in Connecticut are:

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For Remote Amazon Data Science jobs in Connecticut, the most frequently searched job titles are:

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The top searched job categories for Remote Amazon Data Science jobs in Connecticut are:

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Remote Amazon Data Science jobs near you
Infographic showing various Remote Amazon Data Science job openings in Connecticut as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior RWE/RWA Programmer - Remote

Penfield Search Partners

Fairfield, CT • Remote

Full-time

Re-posted 4 days ago

Job description

Job Description Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com No 3rd party candidates Brief Description: The Senior Real-World Analyst (RWA) will be responsible for conducting analyses for Real-World Evidence (RWE) studies utilizing administrative claims, electronic medical records (EMR), and registry data. The successful candidate will possess a deep understanding about the use of Real-World Data (RWD), exceptional programming and analytical skills and a proven track record in delivering high-quality RWE analytic projects. The candidate will also ensure the timeliness and delivery of scientifically valid research

Essential Functions Effectively designs and codes R and SQL programs for assigned project(s), consistently meeting objectives of the project. Clean and validate RWD for consistency and reliability Implement programming as specified from RWE protocol using a variety of RWD from multiple sources, including Optum and Flatiron Leverage advanced statistical and epidemiological methodologies to deliver robust and reliable analyses Create or review and approve programming plans at study and project level. Displays highly advanced knowledge regarding program, epidemiology methodologies implementation and system development life cycle concepts.

Maintain clear documentation of analytical programming and operational definitions to support reproducible and auditable RWE studies Develop dashboards, reports, and presentations to communicate findings Work collaboratively with members of study teams to meet study and recurring report timelines Minimum Requirements MS in data science, epidemiology, statistics, public health or related discipline At least 7 years of RWD analysis experience using healthcare claims/EMR/registry databases within the biopharmaceutical industry or provider/payer organizations Fluence in programming software SQL and R is required. Knowledge of SAS and/or Python would be considered an advantage Optum and Flatiron experience are required Familiarity with US and global health care coding system (e.g. ICD, CPT, HCPCS, LOINC, MedDRA) and delivery system (e.g

payers and reimbursement models) Experience conducting routine and advanced statistical analyses for RWE generation, leveraging time-to-event, cross-sectional, and longitudinal data Experience with big data analytical platforms Deep understanding of observational study analysis Able to work in a fast-paced, flexible, team-oriented environment

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