R Developer

Vintti bridges the staffing gap for US businesses with a unique focus on time zone compatibility. We source top talent from Latin America, offering companies access to professionals who are available during standard US working hours. This alignment eliminates the need for off-hour communications and allows for integrated teamwork, as if all team members were in the same office.

An R Developer specializes in using the R programming language to develop, optimize, and maintain data analysis and statistical computing applications. Typically, these professionals work closely with data scientists, statisticians, and analysts to design and implement data-driven solutions, facilitate data visualization, and perform comprehensive data mining and statistical analysis. They are adept at manipulating large datasets, automating data processing tasks, and creating custom scripts and packages tailored to specific business needs, ultimately providing valuable insights and supporting data-driven decision-making processes within organizations.

- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- Proven experience as an R Developer or in a similar role.
- Strong proficiency in R programming language and RStudio.
- Solid understanding of statistical methods and data analysis techniques.
- Experience with R packages development and maintenance.
- Proficiency in data manipulation and transformation using dplyr, tidyr, data.table, and other relevant packages.
- Experience with R Shiny for creating interactive visualizations and dashboards.
- Familiarity with machine learning libraries and frameworks in R (e.g., caret, randomForest, xgboost).
- Knowledge of data visualization tools such as ggplot2.
- Experience in implementing and validating complex statistical models.
- Proficiency in version control systems, preferably Git.
- Strong problem-solving skills and attention to detail.
- Ability to write clean, efficient, and well-documented code.
- Experience with SQL and database management.
- Familiarity with data extraction tools and techniques.
- Understanding of data security and privacy regulations.
- Excellent communication skills to translate complex data findings into actionable insights.
- Experience with Agile development methodologies.
- Ability to work collaboratively in a team environment.
- Strong organizational and time management skills.
- Continuous learner mentality with a passion for keeping up-to-date with industry trends.
- Experience in conducting and leading code reviews.
- Mentoring experience or demonstrated ability to guide junior developers.

- Write and maintain R code for data analysis and statistical tasks.
- Optimize and update existing R scripts and packages.
- Collaborate with data teams to define and meet analytic requirements.
- Perform data extraction, cleaning, and transformation using R.
- Develop and apply statistical models and machine learning algorithms in R.
- Validate and ensure the accuracy of data sets and analysis results.
- Create visualizations, dashboards, and reports using R Shiny.
- Automate routine data processes with R scripts.
- Review and provide feedback on code written by peers.
- Keep up-to-date with advancements in R programming and data science.
- Document all code, analytical methodologies, and processes thoroughly.
- Troubleshoot and resolve issues in R applications and data pipelines.
- Work with IT and operations to integrate R solutions into business processes.
- Mentor and guide junior developers in R programming and data analysis.
- Participate in Agile project management activities, including sprint planning and daily stand-ups.
- Contribute to building and enhancing internal R packages and tools.
- Assess and implement new technologies to improve R development workflows.
- Ensure data handling complies with security and privacy regulations.
- Conduct exploratory data analysis to identify business opportunities.
- Communicate analytical results to stakeholders effectively.

The ideal candidate for the R Developer role is a highly skilled and experienced professional with a Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field. They have a strong proficiency in R programming and RStudio, coupled with a deep understanding of statistical methods and data analysis techniques. Demonstrating proven experience in developing and maintaining R packages, they are adept at data manipulation and transformation using tools such as dplyr, tidyr, and data.table. Their expertise extends to creating interactive visualizations and dashboards using R Shiny and employing machine learning libraries such as caret, randomForest, and xgboost. The ideal candidate possesses proficiency in version control systems like Git and has significant experience in implementing and validating statistical models. They have a track record of writing clean, efficient, and well-documented code, coupled with a solid understanding of SQL and database management. Excellent problem-solving skills and attention to detail set them apart, along with their commitment to data security and privacy regulations. They are effective communicators capable of translating complex data findings into actionable insights and have experience with Agile development methodologies. The ideal candidate thrives both independently and as part of a collaborative team and possesses strong organizational and time management skills. With a continuous learner mentality, they stay updated with industry trends, driven by a passion for data science and analytics. Their experience in conducting and leading code reviews, as well as mentoring junior developers, showcases their strong leadership capabilities. Enthusiasm for contributing to the team’s success and the company’s goals, along with a proactive problem-solving mindset and commitment to best practices in coding, makes them the perfect fit for this role.

- Write, test, and debug code in the R programming language for various data analysis and statistical tasks.
- Develop, optimize, and maintain R scripts and packages.
- Collaborate with data scientists and analysts to understand requirements and deliver data-driven insights.
- Perform data extraction, cleaning, transformation, and visualization using R.
- Implement complex statistical models and machine learning algorithms using R.
- Ensure the integrity, accuracy, and consistency of datasets through rigorous testing and validation.
- Create interactive dashboards and reports using R Shiny and other visualization tools.
- Automate data workflows and repeatable processes with R scripts.
- Conduct code reviews and provide constructive feedback to peers.
- Stay updated with the latest developments and best practices in R programming and data science.
- Document code, methodologies, and processes clearly and comprehensively.
- Troubleshoot and resolve issues related to R applications and data pipelines.
- Collaborate with cross-functional teams including IT, business analysts, and operations to integrate R solutions into the broader analytics ecosystem.
- Mentor junior developers and provide guidance in R programming and statistical analysis.
- Participate in sprint planning, stand-ups, and other Agile methodologies for project management and delivery.
- Contribute to the development of internal R packages and tools to streamline data processes.
- Evaluate, recommend, and implement new tools and technologies to enhance R development capabilities.
- Ensure compliance with data security and privacy regulations in all data handling processes.
- Conduct exploratory data analysis to uncover patterns and insights that support business strategies.
- Communicate findings and recommendations effectively to technical and non-technical stakeholders through presentations and written reports.

- Strong analytical and critical thinking skills
- Attention to detail and commitment to accuracy
- Excellent communication and interpersonal skills
- Ability to work independently and as part of a collaborative team
- Eagerness to learn and adapt to new technologies and methodologies
- Proactive problem-solving mindset
- Strong organizational and time management abilities
- Passion for data science and analytics
- Commitment to best practices in coding and data analysis
- Effective mentorship and leadership capabilities
- Enthusiasm for contributing to team success and company goals

- Competitive salary and performance-based bonuses
- Comprehensive health, dental, and vision insurance plans
- Generous paid time off (PTO) and holidays
- Flexible work hours and remote work options
- Professional development opportunities, including workshops, conferences, and training programs
- Retirement savings plans with employer contributions
- Life and disability insurance coverage
- Employee wellness programs and resources
- On-site fitness center and wellness activities
- Career advancement opportunities within the company
- Relocation assistance if necessary
- Tuition reimbursement for further education
- Access to cutting-edge technology and tools
- Collaborative and inclusive company culture
- Employee recognition programs and awards
- Paid parental leave and family support programs