Bioinformatics Analyst I
Washington, DC

Job Description

The Bioinformatics Analyst will take on responsibilities for providing broad bioinformatics support for genetics projects, manipulating and representing large-scale phenotypic and genotypic data to support the analysis and presentation of results. Primary responsibilities will be to provide programming expertise to support the spectrum of molecular genetic diagnosis of patients, including the development and application of bioinformatics algorithms to reduce manual tasks, optimize data analysis, and streamline workflows. The position is responsible for the installation, configuration, validation, and maintenance of analytical software packages; performs some programming and scripting to develop software; and assists with data management and transformations. Familiarity with biostatistics, molecular biology, human genetics, the principles of experimental design, and clinical diagnostic laboratory experience is highly desirable. Excellent interpersonal and communication skills are essential, as are the abilities to work both independently and collaboratively and to meet deadlines.

Minimum Education

Bachelor's Degree Bioinformatics, computer science and/or the life science. MS or PhD bioinformatics, computer science and/or the life science preferred.

Minimum Work Experience

2 years

Specific Requirements and Preferences

0-2 years relevant experience if MS or PhD .

Required Skills/Knowledge

Familiarity with genomic technologies (especially Next Generation Sequencing) and their applications, including experimental design considerations.

Familiarity with a wide range of biological database and resources, including but not limited to GenBank, gnomAD, EnsEMLB, the UCSC genome browser, db GAP, Reactome, and other similar resources.

Experience in a clinical laboratory environment and appropriate usage of version and quality control systems is crucial.

Familiarity with implementing supercomputer-based pipelines for the analysis of large datasets and cluster functioning and/or Cloud-Based data management.

Familiarity with laboratory healthcare systems (i.e. LIMS) and ability to program in various APIs is preferred.

Proficiency in programming Python/R/Bash/Snakemake, statistical programming using R or related tools, web-development, and database serialization using JSON/Mongo/SQL as well as ability to prototype software solutions for data analysis is crucial.

Team oriented with excellent written and verbal communication skills, and demonstrated ability to self-education in current bioinformatics techniques and resources.

Functional Accountabilities

Project Management

1. Interprets complex biological information and meets with scientists to provide bioinformatics consultation in the analysis of experimental data

2. Communicates with lab directors to understand and obtain data analysis specifications

3. Design data analysis projects plans and timelines and maintains the appropriate documentation

4. Meets timelines and quality expectations on data analysis related deliverables for multiple projects

5. Works independently and as a team member to analyze data

Data Management

1. Develops, follows, and maintains standard operating procedures or specific scientific protocols

2. Integrates and analyzes data from external resources including genome sequencing projects, functional genomics analysis, and other initiatives

3. Performs data mining and synthesis activities using various internal resources, public database and publications

4. Ensure data integrity and security

5. Ensure that data is backed up in long term storage

Database maintenance

1. Organizes genomics data and developing new data types into databases, displays, or graphic presentations for publications and web presentations.

2. Assists in designing and developing new database to store gene expression, fusion gene and other genomics data files.

3. Maintains and improves existing databases

4. Configures and maintains systems that track progress of clinical samples through wet-bench and computational protocols working with wet ab and research teams

Computational Infrastructure Administration

1. Writes and executes code to extract relevant subsets of expressions data and analyzes these datasets in context of clinical diseases specific information

2. Maintains the computational infrastructure and controls the flow of samples and information for large-scale studies

3. Creates custom toolkits and analytic methods to meet the needs of investigators

4. Recognizes and reports problems with data management process and addresses problems as needed

Organizational Accountabilities

Organizational Accountabilities (Staff)

Organizational Commitment/Identification

1. Anticipate and responds to customer needs; follows up until needs are met

Teamwork/Communication

1. Demonstrate collaborative and respectful behavior

2. Partner with all team members to achieve goals

3. Receptive to others' ideas and opinions

Performance Improvement/Problem-solving

1. Contribute to a positive work environment

2. Demonstrate flexibility and willingness to change

3. Identify opportunities to improve clinical and administrative processes

4. Make appropriate decisions, using sound judgment

Cost Management/Financial Responsibility

1. Use resources efficiently

2. Search for less costly ways of doing things

Safety

1. Speak up when team members appear to exhibit unsafe behavior or performance

2. Continuously validate and verify information needed for decision making or documentation

3. Stop in the face of uncertainty and takes time to resolve the situation

4. Demonstrate accurate, clear and timely verbal and written communication

5. Actively promote safety for patients, families, visitors and co-workers

6. Attend carefully to important details - practicing Stop, Think, Act and Review in order to self-check behavior and performance