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Afternoon Data Analyst R Programming Jobs in Pennsylvania

At least 3 years data analytics experience required At least 3 years of business or operational experience preferred Bachelors in Engineering, Mathematics, Statistics, or Data Science/Analytics ...

The Analyst will act as a liaison between various Data and Engineering stakeholders to develop automated solutions to analyze, correlate and report data and insights to stabilize and scale our self ...

Expertise in Python or R for data manipulation, automation and advanced analytics. * Hands-on experience with data visualization tools like Power BI, Tableau or Looker to create interactive reports.

... , Data, and Software Engineering, servicing an array of noteworthy financial services and ... Conduct data analysis to identify patterns, correlations, and insights. * Collaborate with cross ...

Analyst

Pittsburgh, PA · On-site

$100K - $110K/yr

Experience with data visualization tools (Power BI, Tableau). * Basic programming knowledge (Python or R). * Strong analytical and problem-solving abilities. * Good communication and presentation ...

Senior Data Analyst

Philadelphia, PA · On-site

$86K - $109K/yr

SQL, Python, R). * Strong data analysis skills, with the ability to synthesize data, identify and ... Bachelor's degree with focus on Computer Science, Statistics, Mathematics, Programming, MIS, or ...

Strong proficiency in Python or R for statistical analysis, automation, and machine learning model development. * Experience with cloud-based data platforms such as AWS, GCP, or Azure, including data ...

Data Analyst Position type: FT (Exempt) Location: Administrative Offices Join the CReW! We offer ... This position works closely with Engineering, IT, Operations, and Leadership to support strategic ...

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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.

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 Pennsylvania? The most popular types of Data Analyst R Programming jobs in Pennsylvania are:
What are popular job titles related to Afternoon Data Analyst R Programming jobs in Pennsylvania? For Afternoon Data Analyst R Programming jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Afternoon Data Analyst R Programming jobs in Pennsylvania look for? The top searched job categories for Afternoon Data Analyst R Programming jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Afternoon Data Analyst R Programming jobs? Cities in Pennsylvania with the most Afternoon Data Analyst R Programming job openings:

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Job description

Title of Position: Junior Data Analyst

Location: Fairless Hills, PA (Fully On-Site)

Industry Leading Benefits: Medical, Prescription, Dental, Vision, 401K, Pension, Short- and Long-Term Disability, Life Insurance, Tuition Reimbursement.

Silvi Materials has been expanding our “A” Team of employees since 1947! Our team has grown to 15+ companies, employing over 950 people across 30+ locations in Southeastern Pennsylvania, New Jersey, and North Carolina.  Silvi is large enough to provide the stability you need, but small enough that you can feel your individual contribution to our success.  We value the fresh ideas and perspectives of each new member of our team.

What does Silvi Materials offer you, you may ask?

  • Phenomenal Benefits: Medical, Vision, Dental, Prescription, Vacation, Paid Holidays, and so much more!
  • Your future in mind: With 401(k) (at select locations) and/or pension options. We want all employees to build a great retirement!
  • Growth at Silvi Materials: We offer each employee the opportunity to move into any facet of our complex business. And our tuition reimbursement program is the perfect springboard to help you get there!

So, what does a Junior Data Analyst do?

A Junior Data Analyst extracts, migrates, cleanses, and organizes raw data to ensure accuracy for business intelligence needs. Key responsibilities include data querying, validation, database maintenance, and dashboards development to support team insights.

Key Responsibilities

  • Data Cleaning and Transformation: Clean, interpret, organize, and validate data to ensure accuracy and consistency multiple sources.
  • Database Management: Utilize tools such as SQL and/or Python to query, extract, and maintain databases.
  • Quality Assurance: Identify and resolve data inconsistencies or missing information.  Communicate data validation activities, monitor data quality, and coordinate remediation plans to maintain the accuracy of integrated data.
  • Reporting and Visualization: Conduct data analyses using statistical techniques and data visualization tools.  Identify patterns, trends, and correlations in datasets.  Create and update dashboards, charts, and reports to communicate findings.
  • Documentation: Develop detailed documentation of data processes/flows, decisions, and configurations to meet compliance and training requirements.
  • Collaboration: Partner with technical and functional stakeholders to align data activities with business objectives.
  • Manage deliverables in accordance with project plans.
  • Contribute to the development and review of Standard Operating Procedures (SOPs), ensuring data practices adhere to organizational standards and requirements.
  • Effectively collaborate with stakeholders by translating technical terminology and processes; support drive data driven decision making.
  • Contribute to the development of a complete data lake and/or data warehouse solution.
  • Support the continuous improvement of data quality and data management processes.

Qualifications & Experience

  • Education: Bachelor’s degree in Information Systems, Computer Science, Mathematics, Statistics, Business Administration, Engineering or a related field is required.
  • Technical Proficiency:Proficiency in SQL and Excel is required, with experience in Python or R preferredKnowledge of InterBase scripting is a plus.
  • Analytical Skills:Ability to troubleshoot complex software issues and analyze data to guide decision-making.
  • Understanding of visualization tools such as Power BI.
  • Experience supporting complex system implementations or upgrades is a plus.
  • Ability to collect, organize, and analyze large datasets is a plus.
  • Excellent problem-solving abilities, time management skills, and attention to detail.
  • Experience with ITSM systems like DevOps or Jira is a plus.
  • Experience with data warehouses and/or data lakes is a plus.
  • Knowledge and use of the Microsoft Office Suite is required.
  • Ability to effectively manage multiple priorities in a dynamic environment.

Physical Demands

In a typical work setting, people in this job:

  • Use hands/fingers to type and move office objects
  • Sit for long periods of time
  • Hear sounds and recognize the difference between them
  • See details of objects that are less than a few feet away and far distances
  • See differences between colors, shades, and brightness.
  • Lift 20 pounds on occasion
  • Kneel, stoop, crouch, bend, stretch, twist or crawl, on occasion

Silvi Materials does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor