Key Responsibilities and Required Skills for a Veterinary Research Analyst

🎯 Role Definition

The Veterinary Research Analyst is a pivotal role at the intersection of animal health, data science, and clinical research. This position is responsible for the rigorous analysis, interpretation, and reporting of data generated from veterinary studies. The analyst plays a crucial part in the entire research lifecycle, from study design and protocol development through to data collection, statistical analysis, and the final dissemination of findings. By providing robust evidence and clear insights, the Veterinary Research Analyst directly contributes to the development of new veterinary medicines, treatments, and diagnostic tools, ensuring they are safe, effective, and meet regulatory standards. This role requires a unique blend of scientific knowledge in veterinary medicine, statistical expertise, and strong data management skills to support evidence-based decision-making within the organization.

📈 Career Progression

Typical Career Path

Entry Point From:

Veterinary Technician with a specialization in research or clinical trials.
Data Analyst from a biological or life sciences background.
Academic Researcher or Post-Doctoral Fellow in a related field.

Advancement To:

Senior Veterinary Research Analyst or Principal Analyst.
Clinical Research Manager or Study Director.
Data Scientist, Animal Health.

Lateral Moves:

Medical Science Liaison.
Regulatory Affairs Specialist.
Product Manager, Veterinary Health.

Core Responsibilities

Primary Functions

Design, develop, and review protocols for veterinary clinical and pre-clinical trials, ensuring they have clear objectives and statistically sound methodologies.
Perform complex statistical analyses on diverse datasets from studies to evaluate the safety, efficacy, and performance of new and existing veterinary products.
Author and co-author comprehensive study reports, technical summaries, and regulatory submission documents for agencies like the FDA-CVM, USDA, and EMA.
Develop and maintain sophisticated databases and data management plans to ensure the accuracy, integrity, and accessibility of all research data.
Conduct thorough literature reviews and meta-analyses to synthesize existing scientific knowledge and identify research gaps or support product positioning.
Create compelling data visualizations, dashboards, and presentations to communicate complex research findings effectively to both scientific and non-scientific stakeholders.
Collaborate closely with cross-functional teams, including veterinarians, clinical research associates, statisticians, and regulatory affairs specialists, to ensure study objectives are met.
Interpret and summarize analytical results, providing actionable insights and recommendations to guide project direction and strategic decision-making.
Prepare scientific manuscripts for publication in peer-reviewed journals and develop abstracts and posters for presentation at key industry and scientific conferences.
Ensure all research activities, data collection, and reporting are conducted in strict compliance with Good Clinical Practices (GCP), Good Laboratory Practices (GLP), and other relevant regulatory guidelines.
Develop and validate statistical analysis plans (SAPs) prior to database lock, outlining the specific methodologies to be used for data analysis.
Program, test, and document statistical programs and analysis scripts using languages like SAS, R, or Python for data manipulation and reporting.
Perform ad-hoc data queries and exploratory analyses to answer critical business and research questions from leadership and project teams.
Assist in the oversight of data collection activities at clinical trial sites to ensure protocol adherence and high-quality data capture.
Contribute to the development and implementation of standard operating procedures (SOPs) for data management and statistical analysis.
Analyze and interpret pharmacokinetic (PK) and pharmacodynamic (PD) data to understand drug absorption, distribution, metabolism, and excretion in target animal species.
Provide analytical support for pharmacovigilance and post-market surveillance activities by analyzing safety data to monitor product performance in the field.
Participate in the evaluation and selection of external partners, such as contract research organizations (CROs), for outsourced research activities.
Assist in sample size calculations and power analyses to ensure studies are adequately powered to detect meaningful treatment effects.
Review and provide critical feedback on case report forms (CRFs) and electronic data capture (EDC) systems to optimize data quality and user experience.
Maintain a deep understanding of current trends, techniques, and advancements in veterinary medicine, biostatistics, and data science.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis to inform early-stage research and business development opportunities.
Contribute to the organization's data strategy and roadmap by identifying new analytical tools and methodologies.
Collaborate with business units to translate data needs into engineering requirements for the development of new data pipelines and platforms.
Participate in sprint planning and agile ceremonies within the data engineering and analytics teams to ensure alignment on project priorities and timelines.

Required Skills & Competencies

Hard Skills (Technical)

Statistical Programming: High proficiency in at least one statistical programming language such as R, SAS, or Python for complex data analysis and modeling.
Database Management: Strong experience with SQL for querying, manipulating, and extracting data from relational databases.
Data Visualization: Demonstrated ability to create clear and impactful data visualizations and dashboards using tools like Tableau, Power BI, or R packages (e.g., ggplot2).
Clinical Trial Knowledge: In-depth understanding of clinical trial design, execution, and management, including familiarity with GxP (GCP, GLP) regulations.
Scientific Writing: Proven ability to author technical reports, regulatory documents, and manuscripts for peer-reviewed publication.
Epidemiological Methods: Strong grasp of epidemiological principles and study designs (e.g., cohort, case-control) as applied to animal health.
EDC/CTMS Systems: Experience working with Electronic Data Capture (EDC) and Clinical Trial Management Systems (CTMS) is highly desirable.

Soft Skills

Analytical & Critical Thinking: Exceptional ability to dissect complex problems, interpret multifaceted datasets, and draw logical, evidence-based conclusions.
Meticulous Attention to Detail: A commitment to producing high-quality, accurate work, with a focus on data integrity from collection to reporting.
Communication & Interpersonal Skills: Excellent written and verbal communication skills, with the ability to convey complex technical information clearly to diverse audiences.
Collaboration & Teamwork: A proactive and collaborative mindset, capable of working effectively in cross-functional team environments to achieve shared goals.
Problem-Solving: Resourceful and creative in finding solutions to analytical challenges and overcoming obstacles in research projects.
Project Management: Strong organizational skills with the ability to manage multiple projects concurrently, prioritize tasks, and meet deadlines.

Education & Experience

Educational Background

Minimum Education:

A Bachelor of Science (BS) degree in a relevant scientific or quantitative field.

Preferred Education:

A Master's Degree (MS), PhD, or Doctor of Veterinary Medicine (DVM) is strongly preferred and provides a significant advantage.

Relevant Fields of Study:

Veterinary Science / Animal Science
Biostatistics or Statistics
Epidemiology or Public Health
Data Science or a related quantitative field

Experience Requirements

Typical Experience Range:

3-7 years of professional experience in a data analysis, biostatistics, or clinical research role, preferably within a scientific context.

Preferred:

Direct experience working within the animal health industry (pharmaceuticals, biotech), a veterinary contract research organization (CRO), or an academic institution focused on veterinary or comparative medicine research is strongly preferred. Experience with regulatory submissions to the FDA-CVM, USDA, or EMA is highly valued.