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Entry Level Data Analyst R Programming Jobs in Buffalo, NY

Data Scientist under general supervision will perform data engineering, data modeling and model ... Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.

Data Science Tutor

Buffalo, NY · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Scientist

Boston, NY · On-site +1

Work with engineering teams to operationalize data science workflows, ensuring scalability and ... Are proficient in Python, R, or JavaScript for data analysis and tool development. * Are familiar ...

Associate Data Engineer - AI & Analytics - 2027

Buffalo, NY · On-site

$57K - $57K/yr

... entry-level positions. You'll receive a status update email for each application, so be sure to ... Demonstrated application of programming, data, or analytical skills through coursework, projects ...

... data analysis and integration to support AI-driven initiatives - Utilizing programming languages ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Data Modeler

Buffalo, NY

$53 - $68.75/hr

Our company provides application analysis, design, development and programming, software ... Data Modeler JD: * Requirement analysis skill * Discussion with solution architects and business ...

Expand skills in engineering analysis, validation, and full product design. Progress toward ... and data security will be protected in accordance with applicable laws. We are committed to ...

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Entry Level Data Analyst R Programming information

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How much do entry level data analyst r programming jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for entry level data analyst r programming in Buffalo, NY is $31.89, according to ZipRecruiter salary data. Most workers in this role earn between $20.48 and $35.62 per hour, depending on experience, location, and employer.

What is an entry level data analyst r programming?

An Entry Level Data Analyst (R Programming) is a professional who uses the R programming language to collect, process, and analyze data to help organizations make informed decisions. They typically work with large datasets, create visualizations, and generate reports under the guidance of more experienced analysts. Entry-level data analysts are often responsible for basic data cleaning, statistical analysis, and supporting team projects while they develop their skills in R and data analysis techniques.

What skills and qualifications are needed to thrive as an entry level data analyst r programming?

To thrive as an Entry Level Data Analyst specializing in R Programming, you need a solid grounding in statistics, data cleaning, and analytical methods, typically supported by a relevant degree such as statistics, mathematics, or computer science. Proficiency in R programming, familiarity with data visualization tools (e.g., ggplot2), and experience with spreadsheet software or SQL are commonly required. Strong attention to detail, problem-solving abilities, and clear communication skills set outstanding candidates apart in this role. These skills are crucial to accurately interpret data, deliver actionable insights, and effectively collaborate with teams to support data-driven decision-making.

What are some typical challenges entry level data analysts face when working with R programming in a team setting?

Entry-level data analysts using R often encounter challenges such as adapting to existing codebases, understanding team-specific data workflows, and ensuring code reproducibility and documentation for collaborative projects. New analysts may also need to quickly learn version control practices (like using Git) and follow standardized procedures for data cleaning and reporting. Regular communication with senior analysts and participation in code reviews are essential to build both technical proficiency and teamwork skills.

What is the difference between Entry Level Data Analyst R Programming vs Data Scientist?

AspectEntry Level Data Analyst R ProgrammingData Scientist
Required SkillsBasic R programming, data cleaning, visualization, ExcelAdvanced R, Python, machine learning, statistical modeling
Work EnvironmentBusiness, finance, marketing teamsResearch, tech, healthcare, diverse industries
CertificationsData analysis, R programming coursesData science, machine learning certifications

Entry Level Data Analyst R Programming roles focus on data cleaning, visualization, and basic analysis using R, often within business environments. Data Scientists require advanced statistical and programming skills, including machine learning, and work on complex predictive models across various industries. While both roles involve data handling, Data Scientists typically have a broader skill set and handle more complex projects.

What are the most commonly searched types of Data Analyst R Programming jobs in Buffalo, NY?

The most popular types of Data Analyst R Programming jobs in Buffalo, NY are:

What are popular job titles related to Entry Level Data Analyst R Programming jobs in Buffalo, NY?

For Entry Level Data Analyst R Programming jobs in Buffalo, NY, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Analyst R Programming jobs in Buffalo, NY look for?

The top searched job categories for Entry Level Data Analyst R Programming jobs in Buffalo, NY are:

What cities near Buffalo, NY are hiring for Entry Level Data Analyst R Programming jobs?

Cities near Buffalo, NY with the most Entry Level Data Analyst R Programming job openings:

Infographic showing various Entry Level Data Analyst R Programming job openings in Buffalo, NY as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 80% Full Time, 15% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $66,341 per year, or $31.9 per hour.

Full-time

Re-posted 25 days ago


Job description

We are looking for the right people people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the worlds largest providers of products and services to the global energy industry.

Job Description & Responsibilities:
Data Scientist under general supervision will perform data engineering, data modeling and model deployment.
Analyze large scale complex business data (time series data, structured/unstructured) from various data sources and draw insights
Leverage common open-source Machine Learning/Deep Learning packages for identifying data patterns and/or building predictive models
Conduct statistical analysis to determine trends and significant data relationships
Keep up to date with latest Machine Learning and Artificial Intelligence advancements
Work with data engineers to design and construct data pipelines for reproducible analysis
Leverage cloud computing technologies like Microsoft Azure and distributed computing technologies like Apache Spark
Present results of analyses, including design of graphs, charts, tables, and other data visualizations

Qualifications:
Industry experience in predictive modeling, data science and analysis.
Knowledge of Machine Learning frameworks and packages, including Keras, TensorFlow, Scikit-Learn and cloud computing platforms like Azure.
Experience handling terabyte size datasets, diving into data to discover hidden patterns and using data visualization tools.
Experience writing code in Python, R, Scala, and distributed computing technologies like Spark.
Demonstrated teamwork, strong communication skills, and collaborative in complex engineering projects.
Completion of an undergraduate degree in STEM. Master's degree in STEM is preferred.

Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs.