R&D Data Executive

Working time: Monday- Saturday.
Working location:

Working mainly in Sala office (4 days/ week)
Working in Dong Nai R&D Center 1- 2 days/ week, Having shuttle bus from Sala.

YOUR MISSION:

You will design data collection SOPs, manage data integrity across Genetics and Feed Formulation projects, and deliver dashboards and descriptive analyses that provide actionable insights.
To build and maintain a unified, reliable, and efficient data system for the entire R&D department.
Your mission is to ensure that R&D decisions are grounded in accurate, traceable, and well- structured data, enabling a data- driven culture that supports continuous improvement and innovation.

KEY ACTIVITIES:
Data System Development & Maintenance

Automate data synchronization and reporting wherever possible (e.g., via Power Query, SQL, or Python/R scripts).
Standardize data structures, naming conventions, and version control across teams.
Build and maintain centralized databases and data pipelines covering all R&D experiments (Genetics, Feed Formulation, and Production trials).

SOP Design & Implementation

Develop, document, and continuously improve SOPs for data collection, validation, and transfer.
Monitor compliance with SOPs and coordinate corrective actions when inconsistencies arise.
Train team members on proper data entry, file organization, and metadata recording.

Data Integrity & Quality Control

Establish and enforce data governance standards to ensure accuracy, completeness, and consistency across all R&D datasets.
Maintain traceable records of every dataset version, transformation, and correction.
Implement automated validation and error- flagging tools to detect anomalies early.
Conduct systematic data audits and integrity checks before analysis or reporting.
Coordinate with experiment leads to resolve data discrepancies and close quality gaps.

Data Analysis & Reporting

Develop reproducible analytical workflows or scripts (R, Python, or Excel) to standardize routine analyses.
Collaborate with scientists to interpret results, highlight key findings, and recommend evidence- based actions for R&D optimization.
Test assumptions, analyze variance structures, and confirm model fit for scientific rigor.
Produce comparative summaries and visualizations that translate raw data into clear biological or operational insights.
Apply suitable statistical approaches (e.g., ANOVA, regression, mixed- effects models) to evaluate treatment effects and validate experimental results.

Cross- functional Collaboration & Support

Support project leads with data- driven summaries for management reviews.
Serve as the main data liaison between Genetics, Feed R&D, and Operations teams.
Contribute to planning and design of experiments by advising on data structure and statistical approaches.

WHAT WE NEED FROM YOU
Education & Background

Experience in life sciences or R&D environments is a plus.
Bachelor’s or Master’s degree in Statistics, Mathematics, Bioinformatics, Data Science, or a related quantitative field.
1–3 years of experience in data analytics, statistical modeling, or research data management

Technical Skills

Familiarity with data visualization tools (e.g., Power BI, ggplot2, matplotlib) and descriptive reporting techniques.
Strong proficiency in statistical analysis (ANOVA, regression, mixed models, correlation, etc.) and experimental data validation.
Solid working knowledge of SQL, Excel, and SharePoint for data structuring, integration, and reporting.
Experience with at least one statistical or programming language (e.g., R or Python) for data analysis and visualization.
Understanding of data governance, integrity checks, and reproducibility principles in experimental research.

Analytical & Professional Skills

Collaborative and proactive attitude, with the ability to train and support R&D staff in data handling and interpretation.
Strong mathematical reasoning and ability to design, test, and interpret statistical models.
Excellent documentation and communication skills to translate analytical findings into clear, decision- ready outputs.
Ability to identify trends, anomalies, and actionable insights from complex datasets.
Curiosity and motivation to grow into a lead analytical role supporting Genetics and Feed R&D data systems.
High attention to detail with a methodical, process- oriented mindset.

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Cập nhật gần nhất lúc: 2026-01-23 18:15:03