Description
Department: Data/Scientific Team
Status: Full-Time, Exempt
Reports to: Chief Data/ Scientific Officer
Job Description
The Statistical Geneticist will have an opportunity to make his or her mark within a growing scientific team within 54gene.
S/he will support the research discovery and development activities to transform human genetics and genomics discoveries to therapeutic hypotheses, and effectively communicate results to impact our emerging pipeline.
The successful candidate will have the opportunity to work in a fast-paced and highly collaborative environment and will be responsible for developing and employing rigorous statistical and computational approaches.
S/he will demonstrate experience in genotype-phenotype associations as well as engage fellow scientists and project teams to leverage genomics data in achieving project objectives.
Roles and Responsibilities
Apply and develop robust statistical and computational approaches to analyze whole-exome and whole-genome sequence data in combination with phenotypic or other genomic data to enable disease/target/biomarker identification and evaluation, exploring mechanism of action, and identification of genetic causal links to disease or subtypes of disease
Evaluate and implement statistical methods to integrate, summarize and report genetic, genomic, and other omics data, examples include WGS, WES, GWAS, and RNA-seq
Understand strategies and methods for genotype imputation, haplotyping, relationship inference and/or polygenic risk score estimation
Work collaboratively within a diverse team, and provide learning opportunities for other staff, if and when applicable
Qualifications
Knowledge, Skills & Abilities:
Knowledge of genome-wide analyses and approaches, including quality control options for genomic data, approaches for association analysis in the presence of relatedness or population structure, and approaches for burden-based analyses
Expertise with modern cluster and cloud computing environments and with statistical analysis software (R environment for statistical computing, STATA) and human genetics analysis tools (METAL, GCTA, PLINK or similar)
Ability to learn in a fast-paced work environment
Ability to coordinate and manage tasks and processes with minimal supervision
Strong sense of responsibility with keen attention to details
Good communication skills
Education & Certifications:
M.S or PhD in Biostatistics, Statistical Genetics, Computational Biology, or related field
3+ years’ experience in biostatistics or statistical analysis of DNA sequencing data
Experience:
Knowledge and expertise with whole genome as well as whole exome sequence analysis
Solid foundation in statistical genetics principles and applications, especially population genetics
Demonstrated experience in statistical programming using R and other programming languages (e.g. Python, C/C++, Javascript) on large datasets
Experience designing and analyzing validation experiments for laboratory assays
Effective at communicating insights and presenting concepts to a diverse audience
Ability to work with multidisciplinary teams; Experience collaborating with lab scientists on data generation and analysis
Ability to annotate and explore potential functions of identified variants with publicly available functional datasets or fine-mapping tools
Knowledge of rare variant validation using multiple technologies and publicly available resources
Experience in genome-wide (GWAS) and phenome-wide association studies, especially as they relate to implications in large multi-ethnic cohorts and analysis
Other:
Authorization to work in the Nigeria, the United States, and/or the United Kingdom
Must live in one of the locations listed above
Valid international travel documentation
Occasional domestic and international travel may be required
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Department: Data/Scientific Team
Status: Full-Time, Exempt
Reports to: Chief Data/ Scientific Officer
Job Description
The Statistical Epidemiologist will have an opportunity to make his or her mark within a growing scientific team within 54gene.
S/he will study the current literature and compare to both internal and external genomic datasets to analyze the interplay between genetic biomarkers and environmental factors to further the goal toward identifying diagnostic and therapeutic targets.
Primary responsibilities include but not limited to analyzing next generation sequencing data (e.g., RNA-seq, whole genome/exome sequencing) using bioinformatical and statistical tools and developing new statistical methods to answer biological questions that arise in the research.
This position will involve applying—and possibly developing—statistical and computational methods to high-throughput genetic and genomic data. Within the scientific team, potential projects include whole genome sequence association studies, genome-wide epigenetic association studies, and integrative genomic studies that incorporate sequence and expression data.
The successful candidate will have the opportunity to work in a fast-paced and highly collaborative environment as well as engage fellow scientists and project teams to leverage genomics data in achieving project objectives
Roles and Responsibilities
Genetic & Epidemiological Research:
Conduct literature reviews, identify and analyze scientific studies to assist in developing hypotheses for what to look for in the genetic data
Identify and analyze public health issues and their impact on public policies (as it relates to corporate project objectives)
Apply principles of evidence-based public health, disease surveillance, medical terminology, and biostatistics to datasets
Develop and implement epidemiology studies within the context of the company's research and development and post market programs, including data collection and management strategy, project coordination, research administration and study protocols
Analyze health challenges from multiple perspectives, weighing the pros and cons of alternate courses of action, and making recommendations to the company and clients
Work with program staff and stakeholders to develop and implement process and outcome evaluation related to partnerships, surveillance, and interventions
Assist in identifying potential data sources and collecting, analyzing, and disseminating data for surveillance and evaluation, including performance measures related to interventions and program activities
Access and utilize a variety of data sources for program evaluation and chronic disease surveillance activities
Data Analysis:
Assist with data entry, coding and manage databases
Integrate data from health records and biomarker/genomic/other datasets in specific disease areas to gain deeper insight into patient subpopulations enabling an integrated biomarker strategy and/or target/biomarker discovery or verification
Design and perform a variety of detailed biostatistical analyses and applies knowledge of advanced statistical software (e.g., SAS) to tasks that involve large amount of data or extensive data cleaning
Utilize statistical techniques commonly used in epidemiologic evaluations to interpret and analyze health phenomena
Translate data analysis results, often from large datasets, into actionable information for our clients
Frequent application of computer skills in Microsoft ACCESS, PowerPoint, Excel, Word, and a statistical package such as SAS or SPSS
Collaboratively work in teams of data scientists, geneticists, biostatisticians, statistical programmers, health care professionals, as well as independently, to develop and implement disease surveillance, program assessment/evaluation, and medical informatics
Data mining of existing electronic clinical and genomic data systems
Reports & Publications Support:
Provide written reports summarizing study procedures and results for diverse stakeholders (i.e. statistical programmers, biostatisticians and other related functional areas, and external collaborators)
Prepare technical and non-technical summaries of work, scientific reports and manuscripts for publication in peer-reviewed literature
Data Collection Design & Support:
Support research teams in development of study protocols for ethical and IRB submissions
Assist with development of data collection methods
Support research teams to conduct data collection training sessions
Assist and/or conduct focus groups, data collection as defined by study protocol
Develop and conduct surveys, key informant interviews, and focus groups as appropriate.
Provide technical assistance to program staff and contractors on data collection methods, including focus groups and surveys.
Prepare and conduct training and data presentations for diverse audiences
Qualifications
Knowledge, Skills & Abilities:
Ability to coordinate and facilitate functions of cross-functional teams of professional and support personnel in conducting routine and non-routine epidemiologic evaluations
Computerized database management and statistical software program skills, including SAS required.
Data analysis skills (SAS, SPSS, etc.)
Ability to write and publish scientific manuscripts
Ability to communicate and work with a team, and independently, and with external stakeholders
Excellent skills in written and oral communication
Strong math and statistical skills
Cross-cultural competency; ability to work with a diverse, global team
Ability to learn in a fast-paced work environment
Ability to coordinate and manage tasks and processes with minimal supervision
Strong sense of responsibility with keen attention to details
English fluency; fluency in French is a plus
Education & Certifications:
M.S or PhD in Epidemiology, Genetic Epidemiology, Public Health, Biostatistics, or related field
Minimum 15 credit hours in basic and advanced Biostatistics courses & 15+ credit hours in courses in Epidemiology
Experience:
3 years minimum; 5+ years preferred work experience in the field of Epidemiology
2+ years’ experience of working independently in a multi-disciplinary team is required
Experience with qualitative and quantitative data techniques
Experience writing technical or scientific reports, and documents
Experience in the procurement, curation, organization and/or analysis of large sets of data
Experience using technical software, e.g., SAS or R, ArcGIS, Qualtrics, MS Excel
Experience in the use of R, Python, SQL, Shiny, Jira and other data analysis/performance management tools, preferred
Demonstrated success working in a fast-paced, swiftly changing entrepreneurial environment; experience in a biotech start up, or rapidly growing companies, preferred
Experience working in a company based in multiple locations; global experience preferred
Effective at communicating insights and presenting concepts to a diverse audience
Ability to work with multidisciplinary teams; Experience collaborating with lab scientists on data generation and analysis
Ability to annotate and explore potential functions of identified variants with publicly available functional datasets or fine-mapping tools
Knowledge of rare variant validation using multiple technologies and publicly available resources
Experience in genome-wide (GWAS) and phenome-wide association studies, especially as they relate to implications in large multi-ethnic cohorts and analysis
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