Project Engineer

Data Analyst – R&D Laboratory (Scientific Background)

The Data Analyst – R&D Laboratory will serve as a critical link between scientific research and data-driven decision-making. This role is responsible for analyzing complex experimental and operational data generated within the laboratory environment to generate actionable insights that accelerate research outcomes, improve data integrity, and enhance lab efficiency. The ideal candidate brings a strong foundation in scientific research (e.g., chemistry, biology, or related discipline) combined with advanced data analytics capabilities, enabling effective collaboration with scientists while translating data into meaningful business and scientific insights

Key Responsibilities

Data Analysis & Interpretation:

• Analyze experimental, assay, and analytical data to identify trends, patterns, and anomalies
• Translate complex scientific data into clear, actionable insights for R&D teams
• Support hypothesis generation, experimental design, and data-driven decision-making

Scientific Collaboration:

• Partner closely with scientists, lab managers, and R&D leadership to understand research objectives and data needs
• Provide analytical support for ongoing experiments, clinical development activities, and method development
• Act as a liaison between scientific teams and data/IT functions

Data Management & Integrity:

• Ensure accuracy, consistency, and integrity of laboratory data across systems (e.g., LIMS, ELN)
• Develop and maintain data pipelines, datasets, and reporting structures
• Support data governance and compliance with regulatory standards (e.g., GxP, ALCOA principles)

Visualization & Reporting:

• Develop dashboards and visualizations to communicate key findings and performance metrics
• Automate reporting for lab operations, experiment tracking, and research outcomes
• Present insights to both technical and non-technical stakeholders

Process Improvement & Automation:

• Identify opportunities to improve data capture, analysis workflows, and reporting efficiency
• Implement automation solutions using tools such as Python, R, SQL, or BI platforms
• Support digital transformation initiatives within the R&D function

Qualifications

Education & Experience:

• Bachelor's or Master's degree in Chemistry, Biology, Biochemistry, Pharmaceutical Sciences, or related scientific field (PhD a plus)
• 3–7 years of experience in a laboratory or R&D environment with hands-on scientific work
• Experience transitioning into or working within a data analytics role preferred

Technical Skills:

• Proficiency in data analysis tools (e.g., Python, R, SQL, Excel)
• Experience with data visualization tools (e.g., Tableau, Power BI, Spotfire)
• Familiarity with laboratory systems (e.g., LIMS, ELN, CDS)
• Understanding of statistical analysis and experimental design

Domain Knowledge:

• Strong understanding of laboratory workflows, experimental methods, and scientific data structures
• Experience in pharmaceutical, biotech, or life sciences environments preferred
• Familiarity with regulatory and compliance requirements (GxP, FDA, etc.)

Soft Skills:

• Ability to communicate complex data to scientific and business audiences
• Strong problem-solving and critical thinking skills
• Detail-oriented with a focus on data quality and accuracy
• Collaborative mindset with ability to work cross-functionally

Key Success Metrics:

Quality and accuracy of data analysis supporting R&D decisions

Timeliness and effectiveness of insights delivered to scientific teams

Improvements in lab data workflows and reporting efficiency

Adoption and usability of dashboards and analytics tools

Contribution to accelerating research timelines and outcomes