Statistical Geneticist At 54gene

Job Details

Job Title: Statistical Geneticist At 54gene
Organisation: 54gene
Location: Lagos State
Min Work Experience: 3 year(s)
Qualification: M.Sc, PHD
Industry: Medical/ Health Care/ Pharmaceutical
Course: Biostatistics, Statistical Genetics, Computational Biology, or related field
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54gene was founded in 2019 by Dr. Abasi Ene-Obong to address the significant gap in the global genomics market; Nearly 90% of genetic material used in pharmaceutical research is Caucasian. Only 2% is African, despite the fact that Africans and people of African ancestry are more genetically diverse than all other world populations combined.

We are recruiting to fill the position below:

Job Title: Statistical Geneticist

Location: Lagos
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

Application Closing Date
Not Specified.

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