Position: Population Geneticist
Company: Tensill
Experience required: 3y
Category: Data Science
English level: upper
Published: 2021-05-01T00:00:00+03:00

If you're a world class population geneticist / biostatistician you are warm welcome to join our team and impact the way genetic tests inform people about their health risks. Join an early stage startup with seasoned entrepreneurs and help build family planning and personal health platforms. You will collaborate with the research teams to develop polygenic risk score models in the context of family health and in vitro fertilization.

**Key Responsibilities**
Work with bioinformaticians and engineers to develop and implement polygenic risk score models.
Build and evaluate predictive models on very large genetic datasets using known techniques such as LDpred or novel algorithms.
Design and implement quality control processes around data sources used and data validation processes.
Work with our Clinical Lab Director to make sure all algorithms comply with regulatory standards.

**Qualifications**
Master’s degree or PhD in computational biology, statistics, computer science or a related field. 
Preferred: 3+ years experience in academia or industry analyzing large datasets. 
Background in statistics or algorithm development with applications to human genetics. 
Familiarity with large genetic datasets such as UK Biobank, eMerge, and dbGAP. 
Strong coding skills in Python or R. 
Ability to implement new tools and evaluate open source tools quickly. 
Self starter in statistics and bioinformatics contexts and ability to work in an interdisciplinary team. 
Excellent communication skills. 

**Skills and Experience**
3 years experience using common genomics tools such as plink, Beagle, hail, minimac, samtools, vcftools, bcftools. 
1 years experience in building polygenic risk models, adjusting models to different populations. 
Experience in integrating genomics, proteomics, genotyping and sequencing data types.
2 years experience managing large datasets and computational tasks in a cloud environment (AWS or GCP).
Solid understanding of the Linux environment.