Clinical Scientist - Vaccine

Syneos Health · United States · 1 mo ago

RemoteRemoteAnalystFull-time

Job Responsibilities

Works with Medical Director to develop medical plans (Medical Management Plan, Medical Data Review Plan, and Eligibility Review Plan).
Engages with outside experts/consultants/advisors to coordinate the acquisition of necessary medical/scientific input to prepare the respective medical plans.
Performs regular and ad-hoc medical review of data listings and data visualization as needed; analyzes the data to identify risks and data patterns/trends and supports documentation of medical reviews.
Authors medical data queries and reviews query responses, approves query closure in association with Medical Director.
May assist Medical Director in patient profiles review, scientific review of other study level data, protocol deviation review, creation of Medical Review Summary report as needed.
PARTNERS WITH MEDICAL DIRECTORS FOR MEDICAL DATA REVIEW MEETINGS AND SAFETY REVIEW MEETINGS INCLUDING SLIDE PREPARATION AS NEEDED.
Serves as primary interface between internal team, customers, and vendors in the areas of medical data review and eligibility review.
Collaborates with study team members including Clinical Operations, Data Management, Drug Safety and Pharmacovigilance, and Project Management (set-up and/or lead meetings as appropriate) to identify risks related to data integrity and subject safety.
Escalates ongoing and newly developed study concerns such as at-risk project deliverables and out of-scope tasks to the project leads in a timely manner.
Attends at Trusted Process meetings and may participate in internal and external audits.
Acquires basic understanding and knowledge of ongoing protocol designs and disease related terminology and pathology.
Adheres to all data privacy guidelines, International Committee on Harmonization (ICH), and Good Clinical Practices (GCPs), all enterprise policies, standard operating procedures, work instructions, and project plans.
Adheres to customer policies and standard operating procedures, as required in project plans.

Qualifications

Basic understanding and knowledge of ongoing protocol designs and disease related terminology and pathology.

Adherence to data privacy guidelines, International Committee on Harmonization (ICH), and Good Clinical Practices (GCPs), all enterprise policies, standard operating procedures, work instructions, and project plans.

Adherence to customer policies and standard operating procedures, as required in project plans.

Ability to work independently and manage multiple projects simultaneously.

Strong communication and collaboration skills.

Experience with medical and scientific data analysis and review.

Knowledge of Good Clinical Practices (GCPs) and regulatory requirements.

Ability to work effectively with cross-functional teams.

Basic understanding of statistical methods and data analysis techniques.

Experience with medical and scientific literature.

Ability to manage and prioritize workload effectively.

Strong attention to detail and accuracy.

Ability to work under pressure and meet deadlines.

Basic understanding of medical and scientific terminology.

Ability to communicate complex medical and scientific concepts clearly and concisely.

Basic understanding of data privacy and security regulations.

Ability to work with confidential and sensitive information.

Basic understanding of medical and scientific research methodologies.

Ability to work with medical and scientific databases and software tools.

Basic understanding of medical and scientific ethics and principles.

Ability to work with medical and scientific data from various sources.

Basic understanding of medical and scientific research design and methodology.

Ability to work with medical and scientific data from different countries and regions.

Basic understanding of medical and scientific research funding and grant writing.

Ability to work with medical and scientific data from different types of studies (e.g., clinical trials, observational studies, etc.).

Basic understanding of medical and scientific research publication and dissemination.

Ability to work with medical and scientific data from different types of data sources (e.g., electronic health records, laboratory data, etc.).

Basic understanding of medical and scientific research data management and storage.

Ability to work with medical and scientific data from different types of data formats (e.g., structured data, unstructured data, etc.).

Basic understanding of medical and scientific research data analysis and interpretation.

Ability to work with medical and scientific data from different types of data analysis tools (e.g., statistical software, data visualization tools, etc.).

Basic understanding of medical and scientific research data validation and verification.

Ability to work with medical and scientific data from different types of data validation and verification processes (e.g., peer review, audit trails, etc.).

Basic understanding of medical and scientific research data sharing and collaboration.

Ability to work with medical and scientific data from different types of data sharing and collaboration platforms (e.g., cloud-based data repositories, collaborative research networks, etc.).

Basic understanding of medical and scientific research data governance and compliance.

Ability to work with medical and scientific data from different types of data governance and compliance frameworks (e.g., ISO standards, GCPs, ICH guidelines, etc.).

Basic understanding of medical and scientific research data protection and confidentiality.

Ability to work with medical and scientific data from different types of data protection and confidentiality measures (e.g., encryption, access controls, audit logs, etc.).

Basic understanding of medical and scientific research data security and risk management.

Ability to work with medical and scientific data from different types of data security and risk management strategies (e.g., vulnerability assessments, incident response plans, etc.).

Basic understanding of medical and scientific research data integrity and quality assurance.

Ability to work with medical and scientific data from different types of data integrity and quality assurance processes (e.g., data cleaning, data validation, data verification, etc.).

Basic understanding of medical and scientific research data reliability and validity.

Ability to work with medical and scientific data from different types of data reliability and validity assessments (e.g., data consistency checks, data accuracy checks, data completeness checks, etc.).

Basic understanding of medical and scientific research data reproducibility and replicability.

Ability to work with medical and scientific data from different types of data reproducibility and replicability analyses (e.g., data replication studies, data comparison studies, etc.).

Basic understanding of medical and scientific research data transparency and openness.

Ability to work with medical and scientific data from different types of data transparency and openness initiatives (e.g., open data policies, open science practices, etc.).

Basic understanding of medical and scientific research data accessibility and availability.

Ability to work with medical and scientific data from different types of data accessibility and availability strategies (e.g., data sharing agreements, data usage policies, data access controls, etc.).

Basic understanding of medical and scientific research data interoperability and exchange.

Ability to work with medical and scientific data from different types of data interoperability and exchange mechanisms (e.g., data exchange protocols, data integration technologies, etc.).

Basic understanding of medical and scientific research data standardization and normalization.

Ability to work with medical and scientific data from different types of data standardization and normalization efforts (e.g., data dictionary development, data mapping, data harmonization, etc.).

Basic understanding of medical and scientific research data integration and consolidation.

Ability to work with medical and scientific data from different types of data integration and consolidation strategies (e.g., data federation, data warehousing, data consolidation, etc.).

Basic understanding of medical and scientific research data analysis and interpretation.

Ability to work with medical and scientific data from different types of data analysis and interpretation approaches (e.g., descriptive statistics, inferential statistics, predictive modeling, etc.).

Basic understanding of medical and scientific research data visualization and communication.

Ability to work with medical and scientific data from different types of data visualization and communication techniques (e.g., charts, graphs, dashboards, etc.).

Basic understanding of medical and scientific research data storytelling and narrative.

Ability to work with medical and scientific data from different types of data storytelling and narrative approaches (e.g., case studies, vignettes, narratives, etc.).

Basic understanding of medical and scientific research data ethics and principles.

Ability to work with medical and scientific data from different types of data ethics and principles considerations (e.g., informed consent, confidentiality, privacy, etc.).