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Afternoon Data Analyst R Programming Jobs in Connecticut

Pwc

Data Strategy-Manager

Stamford, CT

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Pwc

Data Strategy-Manager

Hartford, CT

$99K - $232K/yr

... Analytics / Solutions Architect - Azure Data Engineer / Azure Solutions Architect - Google Professional Data Engineer - DAMA CDMP (Certified Data Management Professional) - Informatica Certified ...

Commonfund

AI/ML Development Analyst

Norwalk, CT · On-site

$100K - $150K/yr

Collaborate with cross-functional teams including product, engineering, and data teams to integrate ... Strong analytical, problem-solving, and debugging skills. * Ability to work independently and ...

Berkley

Data Engineer

Greenwich, CT

$128K - $154K/yr

R. Berkley Corporation has grown from a small investment management firm into one of the largest ... Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.

Berkley

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

R. Berkley Corporation has grown from a small investment management firm into one of the largest ... Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.

Berkley

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

R. Berkley Corporation has grown from a small investment management firm into one of the largest ... Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.

Bestex Research

Execution Analyst

Stamford, CT · On-site

Proven programming, statistics, and data analysis skills (e.g., Python, SQL, R) * Strong analytical thinking and a demonstrated interest in solving complex problems * Excellent written and verbal ...

BestEx Research

Execution Analyst

Stamford, CT · On-site

Proven programming, statistics, and data analysis skills (e.g., Python, SQL, R) * Strong analytical thinking and a demonstrated interest in solving complex problems * Excellent written and verbal ...

FCP Euro

Data Engineer

Milford, CT · On-site

$114K - $137K/yr

... R for data processing, automation, and analytics. • Integrate APIs to enable seamless data ... tech. • Strong programming skills in Python, R, and SQL. • Experience with AWS services ...

The Hartford

Data Engineer

Hartford, CT · Hybrid

$100K - $151K/yr

Perform data analysis to ensure quality of data assets. * Perform preliminary exploratory analysis ... Experience in R (preferred), Python, and SQL * Experience in ingesting data from a variety of ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Connecticut

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.

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 Connecticut? The most popular types of Data Analyst R Programming jobs in Connecticut are:
What are popular job titles related to Afternoon Data Analyst R Programming jobs in Connecticut? For Afternoon Data Analyst R Programming jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Connecticut look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Connecticut are:
What cities in Connecticut are hiring for Afternoon Data Analyst R Programming jobs? Cities in Connecticut with the most Afternoon Data Analyst R Programming job openings:
Afternoon Data Analyst R Programming jobs near you
Infographic showing various Afternoon Data Analyst R Programming job openings in Connecticut as of July 2026, with employment types broken down into 1% As Needed, 55% Full Time, 36% Part Time, 1% Temporary, 2% Contract, and 5% Nights. Highlights an 99% Physical, and 1% Remote job distribution.
Software Engineer II - Bioinformatics R&D - Remote

Software Engineer II - Bioinformatics R&D - Remote

SEMA4

Stamford, CT • On-site, Remote

Full-time

Re-posted 7 days ago

Job description

Sema4 is a patient-centered health intelligence company dedicated to advancing healthcare through data-driven insights. Sema4 is transforming healthcare by applying AI and machine learning to multidimensional, longitudinal clinical and genomic data to build dynamic models of human health and defining optimal, individualized health trajectories. Centrellis®, our innovative health intelligence platform, is enabling us to generate a more complete understanding of disease and wellness and to provide science-driven solutions to the most pressing medical needs. Sema4 believes that patients should be treated as partners, and that data should be shared for the benefit of all.
Sema4 is seeking a talented, self-motivated Software Engineer II - Bioinformatics R&D to contribute to cutting-edge translational bioinformatics and clinical product development. As a member of the R&D Bioinformatics department, you will act as a critical member of the Sema4 clinical and research ecosystem focused on innovation, reliability, and quality analysis of high-throughput data at an unprecedented scale. You will use advanced cloud computing technologies to do big data analytics. You will be part of an interdisciplinary team that develops computational methods and pipelines to interpret large-scale human genome and transcriptome sequencing data to understand mutations and mutation processes in cancer and reproductive health and to translate that understanding to clinical utility. You will develop systems for integrating novel informatics and genomics tools and methodologies into clinical products and practices.
RESPONSIBILITIES
  • Carry out software design, coding, testing, debugging, and documentation
  • Automate existing analysis workflows, migrate existing workflows to cloud platforms, and develop new workflows and pipelines for clinical and research projects
  • Develop, implement, and follow best practices in software development, code versioning, software testing, and deployment
  • Collaborate closely with scientists, clinicians, and product managers to design, engineer, and implement analytics pipeline solutions in the Amazon AWS cloud environment
  • Deliver high-quality, well-tested software to the production bioinformatics team for use in clinical products
  • Contribute to bioinformatics research analysis
  • Communicate effectively with collaborators (computational and bioinformatics scientists on R&D and production teams, IT/HPC, clinical lab directors, knowledgebase and curation teams, wet lab staff) to understand and satisfy product and research analysis needs
  • Train and provide support for bioinformatics scientists and other team members in internally developed best practices for software development, testing, and software development lifecycle (SDLC) policies

QUALIFICATIONS
  • M.S. in Computer Science, Computer Engineering, Bioinformatics, Computational Biology, or related fields. B.S. plus equivalent experience will be considered
  • 2+ years of post-graduate software development experience
  • Working in a team, self-motivation, ability to manage multiple tasks simultaneously, ability to solve problems independently
  • Possess strong understanding of computer science fundamentals, algorithms, and software engineering best practices
  • Strong coding proficiency in Python and R programming languages or similar. Experience with multiple coding languages such as Java/Scala is preferred.
  • Programming experience in Unix/Linux environment
  • Experience with Docker or similar software container platform
  • Hands-on experience working with NGS and bioinformatics tools will be a plus, especially GATK and WDL and common NGS data formats (VCF, BAM)
  • Experience working with cloud computing infrastructures will be a plus, especially on Amazon AWS and DNAnexus
  • Developing codebases using distributed version control tools (especially Git) and software issue tracking systems (especially Jira)
  • Excellent communication and interpersonal skills needed for working in an interdisciplinary team of scientists, engineers, and clinicians
  • Well-versed in the art of effective technical communication, especially graphical communication, about systems design and high-complexity datasets

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