As a member of the Content Quality Engineering team, you will use your scientific knowledge, software skills and creativity to assess, ensure, and improve the quality of our rich and diverse biological content and derivative products. Our content is the driving force behind our sophisticated existing and emerging solutions, from our flagship product Ingenuity Pathways Analysis to our newly introduced Ingenuity Variant Analysis. Our solutions use cutting-edge computational techniques to gain insight into biological systems. In particular, you will be responsible for assuring the quality of our variant content workflow including the related development processes, tools, knowledge models, delivery and maintenance in a software development setting. You will work closely with a talented and dedicated team of bioinformaticians, scientists, developers, and product managers to enable our customers to gain extraordinary scientific insights through delightful and enlightening investigative experiences using our products. Training will be provided.
DUTIES AND RESPONSIBILITIES
• Assure the quality of our variant content workflow that is an important source for our variant-based products.
• Ensure methods and algorithms used in the variant content workflow are scientifically valid and technically robust.
• Work with developers to improve the sensitivity and specificity of content retrieval for a wide variety of topics.
• Develop highly visible methods for measuring and communicating the quality of high-impact projects.
• Advocate and provide expert guidance for software development best practices.
• Work with developers to rapidly integrate new features or enhancements with sufficient testing coverage.
• Be a passionate voice of our scientific product customers internally. Evaluate, prioritize and escalate issues as necessary.
• Work with developers and build engineers to incrementally improve and streamline build processes.
KNOWLEDGE, SKILLS AND ABILITIES
• Strong knowledge of genetics.
• Strong programming skills, especially in Perl.
• Experience with PubMed, MeSH, and other NCBI databases.
• Enthusiasm to explore scientific research literature, biological databases, algorithms, and software.
• Excellent critical and analytical thinking, problem solving, and troubleshooting skills.
• Excellent verbal and written communication skills.
• Strong proven ability to self-start, plan, prioritize, and scope work in a fast-paced, dynamic environment.
• Strong attention to detail, thoroughness, and organization.
• In-depth knowledge of software development best practices.
• Enthusiasm to learn and practice new technologies as needed to get the job done.
• Ability to work with diverse cross-functional group of scientists, software developers, product managers, and IT professionals.
• Knowledge of one or more of the following: Information Extraction, Natural Language Processing, Information Retrieval, or data mining.
• In-depth knowledge of a variety of quality controls and software testing techniques.
• In-depth knowledge of a variety of algorithms, computational and statistical techniques.
• Knowledge of one or more of the following: ontology, semantic web, Artificial Intelligence, or expert systems.
• Building and delivering software in Agile, scrum, or XP SDLC.
• 2+ year bioinformatics experience, especially in genomics.
• 3+ years writing Perl
• 1+ years interpreting scientific literature and associated results.
• 2+ years parsing and manipulating large data files.
• 4+ years using Unix and Windows and/or Macintosh operating systems.
• 2+ years writing Java.
• 2+ years experience in one or more of the following: Information Extraction, Natural Language Processing, Information Retrieval, or data mining.
• 1+ years software testing.
• 1+ year automating software using, for example, shell scripts, Ant, or Hudson.
• 1+ year experience with database design and querying.
• Bachelor’s degree or equivalent experience in biology-related field, bioinformatics, or computer science with in-depth knowledge of genetics and molecular biology.
• Graduate degree or equivalent experience in biology-related field, bioinformatics, or computer science with in-depth courses knowledge of genetics and molecular biology.