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Afternoon Data Analyst R Programming Jobs in New York

This position focuses on analyzing source data structures, developing source-to-target mapping ... Proficiency in at least one programming language (Python, R) and machine learning tools ...

Job Responsibilities Monthly collection, preprocessing, and analysis of all cost and usage data for ... programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, Go Educational ...

Job Responsibilities Monthly collection, preprocessing, and analysis of all cost and usage data for ... programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, Go Educational ...

Job Responsibilities Monthly collection, preprocessing, and analysis of all cost and usage data for ... programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, Go Educational ...

Job Responsibilities Monthly collection, preprocessing, and analysis of all cost and usage data for ... programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, Go Educational ...

Job Responsibilities Monthly collection, preprocessing, and analysis of all cost and usage data for ... programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, Go Educational ...

Own analytics-ready datasets and dashboards from requirements through delivery and adoption * Lead ... Partner with data engineering to: * Investigate root causes of data issues and bugs * Prioritize ...

Job Responsibilities Monthly collection, preprocessing, and analysis of all cost and usage data for ... programming languages: R, SQL, Python, Scala, Java, C++, Ruby, PowerShell, Go Educational ...

Data Analyst

New York, NY · On-site

$97K - $130K/yr

Data Analyst Req ID: 10150773 Technology is at the heart of Disney's past, present, and future ... Entertainers and Engineers. We work with every part of The Walt Disney Company's media portfolio to ...

Senior Data Analyst

New York, NY · On-site

$94K - $118K/yr

... programming and analysis skills using R, Stata, Python and/or SAS Experience working in academic or public health research settings, with contribution to scientific publications. Willingness and ...

Senior Data Analyst

Manhattan, NY

$94K - $119K/yr

... programming and analysis skills using R, Stata, Python and/or SAS Experience working in academic or public health research settings, with contribution to scientific publications. Willingness and ...

Required:****10+ yrs exp Data Analyst/Engineer with Financial client experience. Strong SQL, Big data****Required** **NY/NJ locals who can go in person interviews.****Day 1 Onsite in NewYork*

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Afternoon Data Analyst R Programming information

What is an Afternoon Data Analyst R Programming?

An Afternoon Data Analyst specializing in R Programming is a data professional who primarily works afternoon shifts and uses the R programming language to analyze, interpret, and visualize data. Their responsibilities typically include cleaning data, performing statistical analyses, and generating reports to support business decisions. They may work across various industries, collaborating with teams to provide insights and automate data processes using R. Afternoon shifts can be ideal for organizations that operate globally or require data support outside standard business hours. Proficiency in R, statistical techniques, and data visualization tools are essential skills for this role.

What are some common challenges faced by Afternoon Data Analysts working with R Programming, and how can they be addressed?

Afternoon Data Analysts using R Programming often encounter challenges such as handling large datasets efficiently, ensuring code reproducibility, and collaborating with team members across different shifts. To address these, it's helpful to utilize R packages designed for big data (like data.table or dplyr), maintain clear and well-documented scripts, and use version control systems like Git for seamless collaboration. Regular communication with team members during shift handovers and leveraging collaborative tools can also enhance workflow and reduce misunderstandings.

What is the difference between Afternoon Data Analyst R Programming vs Morning Data Analyst R Programming?

AspectAfternoon Data Analyst R ProgrammingMorning Data Analyst R Programming
Required CredentialsBachelor's in Data Science, Statistics, or related field; R programming skillsBachelor's in Data Science, Statistics, or related field; R programming skills
Work EnvironmentTypically in office settings, working during afternoon hoursOffice environment, working during morning hours
Employer & Industry UsageUsed in industries with shift-based operations like finance, healthcareCommon in similar industries, often with flexible scheduling
Search & Comparison IntentPeople comparing different shift roles or schedules in data analysisSimilar search intent focusing on shift timing differences

The main difference between Afternoon Data Analyst R Programming and Morning Data Analyst R Programming lies in their work hours. Both roles require similar skills, credentials, and are used in comparable industries. The choice depends on personal schedule preferences and employer shift structures.

Is data science dead in 10 years?

Data science, including roles like an Afternoon Data Analyst using R programming, is expected to remain relevant as organizations continue to rely on data-driven decision making. Advances in automation and AI may change specific tasks, but skills in data analysis, statistical methods, and programming will continue to be valuable in the foreseeable future.

What are the key skills and qualifications needed to thrive as an Afternoon Data Analyst specializing in R Programming, and why are they important?

To thrive as an Afternoon Data Analyst specializing in R Programming, you need a strong background in statistics, data analysis, and proficiency with R, often supported by a degree in a quantitative field. Experience with data visualization tools, R packages (like tidyverse), and familiarity with databases or version control systems (such as Git) is typically required. Critical thinking, attention to detail, and effective communication are essential soft skills for interpreting results and presenting insights to stakeholders. These skills ensure accurate data-driven decisions, efficient workflow, and the ability to translate complex data into actionable business strategies.
What are the most commonly searched types of Data Analyst R Programming jobs in New York? The most popular types of Data Analyst R Programming jobs in New York are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in New York look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in New York are:
What cities in New York are hiring for Afternoon Data Analyst R Programming jobs? Cities in New York with the most Afternoon Data Analyst R Programming job openings:
Data Harmonization Analyst

Data Harmonization Analyst

NYULMC

New York, NY • On-site

Full-time

Medical, Retirement

Posted 26 days ago


NYU Langone Health rating

8.6

Company rating: 8.6 out of 10

Based on 246 frontline employees who took The Breakroom Quiz

11th of 870 rated healthcare providers


Job description

Job Description
NYU Grossman School of Medicine is one of the nation's top-ranked medical schools. For 175 years, NYU Grossman School of Medicine has trained thousands of physicians and scientists who have helped to shape the course of medical history and enrich the lives of countless people. An integral part of NYU Langone Health, the Grossman School of Medicine at its core is committed to improving the human condition through medical education, scientific research, and direct patient care. At NYU Langone Health, equity and inclusion are fundamental values. We strive to be a place where our exceptionally talented faculty, staff, and students of all identities can thrive. We embrace inclusion and individual skills, ideas, and knowledge.
For more information, go to med.nyu.edu, and interact with us on LinkedIn, Glassdoor, Indeed, Facebook, Twitter and Instagram.
Position Summary:
We have an exciting opportunity to join our team as a Data Science Analyst/Engineer.
As part of the Complement-ARIE program, the NYU-Sage New Approach Methodologies (NAMs) Data Hub and Coordinating Center will create a controlled access platform for researchers to share and analyze data resulting from NAMs approaches. The program will build tools to standardize and harmonize NAMs data, store it securely, and provide researchers with powerful analytical and visualization tools. The successful candidate will support implementation of integrated standards [SG1.1]tailored for NAMs data. This position focuses on analyzing source data structures, developing source-to-target mapping specifications, authoring ETL functional requirements and data quality assurance frameworks, and ensuring that harmonization workflows are well-defined, reproducible, and aligned with FAIR data principles. The role is analytical and specification-oriented: the Data Analyst designs and documents the logic that guides implementation, rather than executing engineering tasks directly.
Job Responsibilities:
  • Analyze source NAMs datasets (such as transcriptomics, proteomics, microscopy, imaging, electrophysiology, etc.) to characterize data structure, content, and quality prior to harmonization
  • Develop detailed source-to-CDM mapping specifications, including transformation rules, value set crosswalks, and handling of edge cases
  • Author functional ETL requirements and data flow documentation to guide pipeline development by engineering staff
  • Design data quality assurance (QA) frameworks and acceptance criteria for NAMs datasets, including completeness, conformance, and plausibility checks
  • Evaluate and document terminology alignment across existing Vocabularies, Metadata requirements, and source ontologies
  • Conduct mapping gap analyses and propose remediation strategies for non-standard or missing terminology coverage
  • Collaborate with the Lead Metadata and Standards Specialist to ensure mapping outputs align with metadata standards
  • Produce and maintain clear analytical documentation: data dictionaries, mapping catalogs, QA specification sheets, and implementation guide
  • Support onboarding of new data contributors by reviewing their data structures and advising on harmonization pathways
  • Participate in data quality review cycles, analyze QA outputs, and document findings and recommended remediation steps

Minimum Qualifications:
To qualify you must have a Masters degree in a quantitative discipline (Biomedical Informatics, Computer Science,
Machine Learning, Applied Stascs, Mathematics or similar field) and 3 years of
experience in machine learning/ data science.
Proficiency in at least one programming language (Python, R) and machine learning tools
(scikitlearn, R)
Knowledge of predictive modeling and machine learning concepts, including design,
development, evaluation, deployment and scaling to large datasets
Familiarity with computing models for big data Hadoop / MapReduce, Spark etc.
Knowledge of databases (Relational / SQL, NOSQL MongoDB etc.)
Good grasp of soware engineering principles. Experience in integrating modern
software architectures.
Knowledge and some experience in operational aspects of soware development and
deployment, including automation, testing, virtualization and container technology
Knowledge of clinical and operational aspects of healthcare delivery.
Excellent written and oral communication skills for a variety of audiences
Preferred Qualifications:
Experience with OMOP Common Data Model or other biomedical research CDMs
Experience with programming languages (Python, JAVA, R)
Familiarity with healthcare or life sciences data standards (UMLS, SNOMED-CT, LOINC), or sequencing data standards (FASTQ, BAM, VCF), etc.
Knowledge of FAIR data principles and metadata standards
Familiarity with NAMs methodologies or preclinical research data
Experience with federated data networks or distributed query systems
Familiarity with AI/ML tools applied to terminology matching, automated mapping recommendations, or data quality assessment
Qualified candidates must be able to effectively communicate with all levels of the organization.
NYU Grossman School of Medicine provides its staff with far more than just a place to work. Rather, we are an institution you can be proud of, an institution where you'll feel good about devoting your time and your talents. At NYU Langone Health, we are committed to supporting our workforce and their loved ones with a comprehensive benefits and wellness package. Our offerings provide a robust support system for any stage of life, whether it's developing your career, starting a family, or saving for retirement. The support employees receive goes beyond a standard benefit offering, where employees have access to financial security benefits, a generous time-off program and employee resources groups for peer support. Additionally, all employees have access to our holistic employee wellness program, which focuses on seven key areas of well-being: physical, mental, nutritional, sleep, social, financial, and preventive care. The benefits and wellness package is designed to allow you to focus on what truly matters. Join us and experience the extensive resources and services designed to enhance your overall quality of life for you and your family.
NYU Grossman School of Medicine is an equal opportunity employer and committed to inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration. We require applications to be completed online.
View Know Your Rights: Workplace discrimination is illegal.
NYU Langone Health provides a salary range to comply with the New York state Law on Salary Transparency in Job Advertisements. The salary range for the role is $84,577.93 - $126,991.52 Annually. Actual salaries depend on a variety of factors, including experience, specialty, education, and hospital need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.
To view the Pay Transparency Notice, please click here

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