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Afternoon Data Analyst R Programming Jobs in Mainland, PA

Sr. Data Analyst

Paoli, PA · On-site

$84K - $106K/yr

Bachelor's degree in Finance, Accounting, Economics, Business, Engineering, Data Analytics, or a related field * 4 to 7 years of experience in management consulting, investment banking, private ...

Sr. Data Analyst

Paoli, PA

$84K - $106K/yr

Bachelor's degree in Finance, Accounting, Economics, Business, Engineering, Data Analytics, or a related field * 4 to 7 years of experience in management consulting, investment banking, private ...

Sr. Data Analyst

Paoli, PA · On-site

$84K - $106K/yr

Bachelor's degree in Finance, Accounting, Economics, Business, Engineering, Data Analytics, or a related field * 4 to 7 years of experience in management consulting, investment banking, private ...

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 ...

Showing results 41-60

Afternoon Data Analyst R Programming information

See Mainland, PA salary details

$33.1K

$80.5K

$132.5K

How much do afternoon data analyst r programming jobs pay per year?

As of Sep 12, 2026, the average yearly pay for afternoon data analyst r programming in Mainland, PA is $80,521.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,900.00 and $94,500.00 per year, depending on experience, location, and employer.

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 the key skills and qualifications needed to thrive as an afternoon data analyst specializing in R programming?

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 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 cities near Mainland, PA are hiring for Afternoon Data Analyst R Programming jobs?

Cities near Mainland, PA with the most Afternoon Data Analyst R Programming job openings:

Infographic showing various Afternoon Data Analyst R Programming job openings in Mainland, PA as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $80,521 per year, or $38.7 per hour.

Data Analyst, Fraud Data & Analytics

Malvern, PA

Vangard, Inc.
Convention and Trade Show Organizers • 11 - 50 employees

Full-time

Posted 2 days ago

New


Job description

Responsibilities:

  • Executes fraud analytics assignments from requirements gathering and data assessment through analysis, implementation support, measurement, and monitoring.

  • Develops, tests, and maintains offline fraud detections that generate actionable leads for investigative teams, with guidance on more complex efforts.

  • Monitors detection performance using measures such as precision, false-positive rates, alert volumes, loss exposure, and prevented or avoided impact.

  • Analyzes account, client, transactional, and case data to identify emerging fraud trends, anomalous behavior, common attributes, and fraud signatures.

  • Provides analytical and forensic support for fraud incidents, control gaps, emerging typologies, and other priority investigations.

  • Develops and maintains dashboards, recurring reports, loss reporting, benchmarking analyses, and fraud performance products.

  • Performs data quality checks and validates the completeness, accuracy, and reasonableness of data used in reporting and detections.

  • Documents analytical methodologies, assumptions, data lineage, testing results, and operating procedures in accordance with established standards.

  • Translates analytical findings into clear, actionable insights for fraud operations, risk partners, technology teams, and other stakeholders.

  • Collaborates with senior analysts and business partners to validate analytical approaches, resolve data issues, and deliver quality work products.

  • Partners with investigative teams to obtain disposition feedback and identify opportunities to improve detection effectiveness.

  • Contributes to cross-functional fraud initiatives, data modernization efforts, and evaluation of fraud tools or capabilities.

  • Participates in special projects and performs other duties as assigned.

Qualifications

  • Minimum of five years related work experience.

  • Undergraduate degree or equivalent combination of training and experience.

  • Intermediate SQL skills, including experience querying, joining, validating, and analyzing large datasets.

  • Working proficiency in Python or another analytical programming language used for data preparation, automation, statistical analysis, or detection development.

  • Experience developing and maintaining dashboards and reports in Tableau or a comparable visualization platform.

  • Experience supporting the development, testing, monitoring, or optimization of fraud detections, risk rules, anomaly-detection methods, or analytical models.

  • Working knowledge of analytical validation methods, data quality controls, and performance measurement.

  • Ability to communicate technical findings clearly and provide actionable insights to technical and non-technical audiences.

  • Ability to manage assigned work, maintain documentation, and deliver quality results within established timelines.

  • Knowledge of financial-services fraud typologies, investigations, fraud operations, or fraud loss measurement preferred.

  • Experience working in cloud-based data environments and with governed enterprise data assets preferred.

Global Risk and Security (GR&S) at Vanguard enables business strategy, protects client and Vanguard interests (e.g. assets and data), and stewards a strong risk culture. Our teams leverage enterprise-wide insights, deep expertise, and trusted advice so that across Vanguard leaders and crew drive faster, stronger, risk-informed decisions.

Within GR&S, the Enterprise Security and Fraud (ES&F) sub-division is responsible for the global protection of Vanguard crew, property, data, and client assets. We are the trusted advisors that protect the pride of Vanguard with state-of-the-art security and fraud capabilities. We are a world-class destination of highly engaged, passionate, and diverse talent expected to continuously learn and develop in an ever-changing security landscape. Our crew are our greatest resource - by joining our team you will build collaborative long-term relationships and enjoy a suite of benefits that includes comprehensive health and wellness care, work-life balance, and an investment in your future at its core.

Special Factors

Sponsorship

Vanguard is not offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission-we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.