Associate Data Science Analyst -Hematology Research

Our lab is interested in somatic mosaicism in hematopoietic stem and progenitor cells, both age-related and context relevant in patients with bone marrow failure syndromes. These somatic variants commonly involve epigenetic regulator genes such as TET2, DNMT3A and ASXL1.  This is also referred to as clonal hematopoiesis and is associated with an increased risk of hematological malignancies, as well as an increased all-cause mortality risk. We maintain a large molecularly annotated patient database/ biorepository and our work has direct patient impact. Our research implements bulk and single cell methodologies to better define clonal fitness, clonal dynamics and clonal evolution.  We are particularly interested in the applicability of single cell sequencing to understand the impact of somatic mosaic variants on hematopoiesis and oncogenesis.

An Associate Data Science Analyst position is available for a highly motivated candidate with a background in bioinformatics and a passion for exploring epigenomic alterations in cancer progression using the single cell and bulk high-throughput RNA-sequencing, ChIP-Seq, ATAC-Seq, etc. approaches. Projects will focus on the biology and epigenomics of clonal hematopoiesis and myeloid malignancies with a goal to understand epigenetic determinants that govern clonal fitness and clonal progression.

The candidate must have training in statistics and programming expertise, in particular R/Python and interest in the application of computational/statistical methods to complex datasets, relevant experience with single cell data analysis is a plus. The successful applicant will join a collaborative, interdisciplinary team and perform cutting-edge translational research.

Other responsibilities:
• Provides data insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data. 
• Has basic expertise in the data science methods used to analyze data, and knowledge of data types, topics, and scientific challenges and approaches. 
• Executes analytical procedures in the framework of a specific project work request.
• Modifies scripts or software applications to support data management, data extraction and data analysis as required.
• Contributes to the interpretation of data analysis and to writing reports. 
• May help customers understand the data set and provide training and suggestions for improvement on the data request.
• Leverages communication and interpersonal skills and works with subject matter experts
Presents findings in easy to understand terms for the business or clinical practice.

Qualifications 

Bachelor’s degree in a domain-relevant field such as engineering, mathematics, computer science, statistics, physics, data science, health science, or other analytical/quantitative field.

Ability to develop predictive models to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques, is preferred. Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. machine learning, statistical packages, modeling, etc.) is required. Incumbent must stay current on healthcare trends and enterprise changes. Interpersonal skills and time management skills are required. Requires strong analytical skills and a commitment to customer service.

 

Preferred Qualifications:

 

• An advanced degree in an area of computational biology, bioinformatics, biostatistics, data science, or a related field is preferred.
• Familiar with raw sequencing data (FASTQ) as well as other common formats (SAM/BAM, BED, etc.), command-line tools (bwa, samtools, bedtools, etc.) and biological databases (cBioportal, COSMIC…).
• Working knowledge of Unix/Linux, command line interfaces is preferred.
• Fluency in R and/ or Python.
• Familiar with public databases and resources available for bioinformatics analysis is preferred.
• Experience with genome scale or big data analysis derived from Next Generation Sequencing, including some of the following: bulk and single cell RNA-Seq, scDNA-Seq, CITE-Seq and multi-omics integration.
• Ability to work independently and to show initiative within a team is preferred. 
• Ability to communicate effectively is necessary. 
• Excellent attention to detail is necessary. 
• Position is hybrid with remote work possible but ability to commute/relocate to Rochester, MN  is preferred.

Why Mayo Clinic
Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic. You’ll thrive in an environment that supports innovation, is committed to ending racism and supporting diversity, equity and inclusion, and provides the resources you need to succeed.