Statistical Programmer – Research Data Processing
MNC JOBS INFO
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Descripción de la vacante
MNC JOBS INFO is seeking a detail-oriented Statistical Programmer – Research Data Processing to support research projects through accurate data processing, statistical programming, data validation, and analytical reporting.
The successful candidate will work with research teams, statisticians, data analysts, and other stakeholders to transform raw research data into structured, reliable, and analysis-ready datasets.
Formación
- Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, Biostatistics, IT, or related field preferred.
- Master's degree in Statistics, Biostatistics, Data Science, or related field may be advantageous.
- Relevant coursework/training in statistical analysis, research methodology, programming, or data management is beneficial.
- Equivalent practical experience and demonstrated programming skills may be considered depending on project requirements.
Responsabilidades
- Develop, execute, and maintain statistical programs to process, transform, organize, and analyze research datasets.
- Convert raw data from multiple sources into structured datasets suitable for statistical analysis and reporting.
- Write efficient, readable, and reusable programming scripts using SAS, R, Python, or similar tools.
- Perform data cleaning, recoding, transformation, merging, sorting, and aggregation per approved specifications.
- Implement statistical procedures and computational methods to support research objectives.
- Develop standardized workflows to improve consistency, efficiency, and reproducibility.
- Review incoming datasets for completeness, accuracy, consistency, and suitability for analysis.
- Prepare data structures, data dictionaries, variable definitions, and processing documentation.
- Identify missing values, duplicates, invalid entries, outliers, and inconsistencies in data.
- Maintain organized datasets, programming files, version histories, and supporting records.
- Ensure data processing activities follow project protocols and procedures.
Conocimientos
Educación
Herramientas
Descripción del empleo
MNC JOBS INFO is seeking a detail-oriented and analytical Statistical Programmer – Research Data Processing to support research projects through accurate data processing, statistical programming, data validation, and analytical reporting. The successful candidate will work with research teams, statisticians, data analysts, and other stakeholders to transform raw research data into structured, reliable, and analysis-ready datasets.
This role is suitable for professionals interested in statistical computing, research methodology, data quality management, and evidence-based decision-making. The selected candidate will contribute to the development, testing, and maintenance of statistical programs that support research studies, generate meaningful insights, and ensure consistency throughout the data processing lifecycle.
The ideal candidate should have a strong understanding of statistical concepts, programming techniques, data manipulation, and quality assurance practices. Familiarity with tools such as SAS, R, Python, SQL, or similar statistical programming technologies will be valuable. Candidates should demonstrate a commitment to accuracy, confidentiality, reproducibility, and continuous improvement.
Depending on project requirements, the position may involve collaboration with cross-functional teams in clinical research, academic research, market research, public health, business analytics, or other data-driven environments.
- Develop, execute, and maintain statistical programs to process, transform, organize, and analyze research datasets.
- Convert raw data from multiple sources into structured datasets suitable for statistical analysis and reporting.
- Write efficient, readable, and reusable programming scripts using appropriate statistical programming languages and tools.
- Perform data cleaning, recoding, transformation, merging, sorting, and aggregation according to approved specifications.
- Implement statistical procedures and computational methods to support research objectives.
- Develop standardized programming workflows to improve consistency, efficiency, and reproducibility.
- Review incoming datasets for completeness, accuracy, consistency, and suitability for analysis.
- Assist in preparing data structures, data dictionaries, variable definitions, and processing documentation.
- Identify missing values, duplicate records, invalid entries, outliers, and inconsistencies in research data.
- Apply approved data management rules and document all relevant transformations.
- Maintain organized datasets, programming files, version histories, and supporting records.
- Ensure that data processing activities follow applicable project protocols and organizational procedures.
- Conduct systematic quality checks to verify the accuracy and integrity of processed datasets.
- Compare programming outputs against source data, approved specifications, and expected results.
- Investigate discrepancies, programming errors, and unexpected statistical outputs.
- Develop validation scripts and testing procedures to identify data processing issues.
- Support independent code reviews and quality control activities where required.
- Maintain clear records of identified issues, corrective actions, and validation outcomes.
- Assist statisticians and researchers in preparing analysis-ready datasets, summary tables, and statistical reports.
- Generate descriptive statistics, frequency distributions, cross-tabulations, and other outputs as requested.
- Support the preparation of tables, listings, figures, and research summaries using approved methodologies.
- Ensure that statistical outputs are traceable to the source data and corresponding programs.
- Help interpret data processing requirements and translate them into practical programming solutions.
- Respond to feedback from research teams and revise programs or outputs when necessary.
- Work closely with statisticians, data managers, researchers, and project coordinators to clarify requirements.
- Participate in project meetings, programming reviews, and research planning discussions.
- Communicate technical issues, project risks, and data quality concerns clearly.
- Follow project timelines and provide regular updates on assigned deliverables.
- Contribute to the improvement of programming standards, templates, and documentation practices.
- Maintain the confidentiality and security of research information throughout the project lifecycle.
- A bachelors degree in Statistics, Mathematics, Computer Science, Data Science, Biostatistics, Information Technology, or a related discipline is preferred.
- A masters degree in Statistics, Biostatistics, Data Science, or a related field may be advantageous for advanced research assignments.
- Relevant coursework or training in statistical analysis, research methodology, programming, or data management is beneficial.
- Equivalent practical experience and demonstrated programming skills may be considered, depending on project requirements.
- Knowledge of statistical programming languages such as SAS, R, or Python.
- Familiarity with SQL and relational databases for data extraction, transformation, and validation.
- Understanding of statistical concepts, including descriptive statistics, probability, sampling, distributions, and hypothesis testing.
- Ability to clean, manipulate, validate, and structure datasets from different sources.
- Familiarity with spreadsheets and data analysis tools, including Microsoft Excel.
- Understanding of data quality assurance, reproducible analysis, and programming documentation.
- Basic knowledge of data visualization and statistical reporting techniques.
- Familiarity with Git or other version control systems is an advantage.
- Experience with clinical research standards or regulated research environments is beneficial for relevant projects.
- Strong analytical and problem-solving abilities.
- Excellent attention to detail and numerical accuracy.
- Good written and verbal communication skills.
- Ability to interpret technical specifications and follow established procedures.
- Strong organizational skills and the ability to manage multiple assignments.
- Willingness to learn new statistical tools, programming techniques, and research practices.
The required experience will depend on the complexity of the research projects and the level of the position.
- Fresh graduates with relevant academic knowledge and practical programming skills may be considered for suitable junior opportunities.
- Academic projects, internships, research assignments, or independent data analysis projects are valuable.
- Candidates should demonstrate a basic understanding of statistical methods and the ability to write and test simple programs.
- Familiarity with at least one statistical programming language is desirable.
- Approximately 1–3 years of experience in statistical programming, research data processing, data analytics, or a related role is preferred for many intermediate-level assignments.
- Experience with complex datasets, data validation, programming documentation, and statistical reporting is beneficial.
- Previous collaboration with research teams, data managers, or statisticians is an advantage.
- Experience in clinical trials, pharmaceutical research, public health, or other regulated environments may be required for specialized projects.
- Candidates should be able to demonstrate their technical abilities, problem-solving approach, and commitment to producing accurate and reproducible results.
Working arrangements will depend on the assigned project, team requirements, and employment agreement.
Employment Type: Full-time or project-based, depending on the vacancy.
Work Arrangement: On-site, hybrid, or remote, where available and approved.
Typical Schedule: Approximately 40 hours per week for a standard full-time position.
Working Days: Generally Monday to Friday, subject to organizational policies.
Flexibility: Occasional adjustments to working hours may be required to meet project deadlines or coordinate with international research teams.
Meetings and Reporting: Employees may be expected to attend project meetings, progress reviews, and quality assurance discussions.
The confirmed work schedule, location, and employment terms will be communicated during the recruitment process.
- Understanding of fundamental statistical methods and research data interpretation.
- Ability to recognize data patterns, inconsistencies, and potential quality issues.
- Knowledge of data preparation techniques and statistical reporting requirements.
- Awareness of the importance of appropriate analytical methods and documented assumptions.
- Ability to develop, debug, test, and maintain statistical programs.
- Capacity to translate research requirements into structured programming workflows.
- Understanding of data structures, variables, data types, and logical operations.
- Ability to improve program efficiency while maintaining accuracy and readability.
- Willingness to adopt new technologies and programming standards.
- Ability to maintain clear, reproducible, and well-documented programming workflows.
- Strong commitment to data integrity, confidentiality, and quality control.
- Ability to identify errors, investigate root causes, and implement appropriate corrections.
- Understanding of the importance of audit trails and version control in applicable research settings.
- Ability to explain technical findings in a clear and professional manner.
- Confidence in collaborating with colleagues from technical and non-technical backgrounds.
- Willingness to receive feedback and participate in code reviews.
- Ability to manage priorities, meet deadlines, and work independently when appropriate.
- Demonstrate integrity, accountability, and a consistent commitment to quality.
- Handle sensitive research data responsibly.
- Follow applicable data protection requirements and organizational policies.
- Maintain a proactive approach to learning and professional development.
MNC JOBS INFO aims to attract professionals who value technical growth, meaningful research contributions, and opportunities to develop their expertise. Depending on the confirmed employment arrangement and applicable company policies, potential benefits may include:
Competitive compensation based on experience, technical skills, and role responsibilities.
Opportunities to work on research and data processing projects across relevant industries.
Exposure to statistical programming tools and modern data analysis workflows.
Professional development opportunities through training and practical project experience.
Opportunities to strengthen programming, analytical, and research documentation skills.
Collaborative working environments that encourage knowledge sharing and continuous learning.
Potential access to flexible or remote working arrangements for eligible positions.
Opportunities to take on greater responsibilities as technical expertise develops.
Performance feedback and professional growth discussions.
Applicable leave, insurance, retirement, or other employment benefits according to the actual employment contract and local policies.
Specific benefits, compensation, and eligibility will be confirmed by the recruiting organization. No benefit or remote-work arrangement should be considered guaranteed unless it is explicitly stated in the official offer.
Build practical expertise in statistical programming, data transformation, quality assurance, and reproducible research workflows. Depending on project assignments, you may gain experience with SAS, R, Python, SQL, and other analytical technologies.
Your work will help researchers and analysts access accurate, consistent, and well-organized datasets. High-quality data processing is essential for producing dependable results and supporting informed decisions.
Depending on available projects, you may gain exposure to different research domains, methodologies, and data structures, broadening your technical knowledge and professional experience.
Develop a foundation for future opportunities in statistical programming, biostatistics, data analytics, research data management, statistical consulting, or data science.
Strengthen your ability to solve problems, validate results, document processes, and collaborate with professionals who depend on reliable data.
The role encourages continuous learning, practical problem-solving, and the adoption of better programming practices as tools and research requirements evolve.
MNC JOBS INFO welcomes candidates who are curious, analytical, responsible, and committed to producing accurate and meaningful research data outputs.
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