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Protein Library Design Data Scientist

Company Description

Join us and make YOUR mark on the World!

Are you interested in joining some of the brightest talent in the world to strengthen the United States’ security? Come join Lawrence Livermore National Laboratory (LLNL) where our employees apply their expertise to create solutions for BIG ideas that make our world a better place.

We are committed to a diverse and equitable workforce with an inclusive culture that values and celebrates the diversity of our people, talents, ideas, experiences, and perspectives. This is important for continued success of the Laboratory’s mission.

Pay Range

$117,180 - $148,608 Annually for the SES.1 level
$140,700 - $178,392 Annually for the SES.2 level

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage.  An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs.

Job Description

We have an opening for a Data Scientist focusing on protein library data design, analysis, and dissemination. This role requires an interdisciplinary approach, including strong knowledge of data science, machine learning, and biological data. You will have a supporting role in external and internal library efforts. You will execute design, analysis, tool-building and also collaborate toward effective, efficient, and rapid library data generation. You will communicate with internal and external teams generating and using this data, as well as other members of this team who design, analyze, and disseminate data and produce tools to do so more efficiently in the future. This position will be in the Computational Engineering Division (CED), within the Engineering Directorate.

This position will be filled at either level based on knowledge and related experience as assessed by the responsibilities (outlined below) will be assigned if hired at the higher level.

You will

  • Serve as a member of a team for library design and contribute to the fulfillment of technical projects and organizational objectives.
  • Collaborate with team members to provide input on deliverables  and to regularly communicate the status and projected delivery date to ensure quality results are provided in accordance with established deadlines.
  • Contribute, participate, and work in coordination with internal team members to continue and expand the design, generation, analysis, and dissemination of library data, as well as the development of effective library design workflows  .
  • Work independently under general direction to solve problems of limited complexity using standard techniques and methodologies.
  • Respond to needs in library design by using fundamental knowledge and adhering to defined practices and procedures.Perform other duties as assigned.
  • Perform other duties as assigned.

Additional job responsibilities, at the SES.2 level

  • Work under limited direction using independent judgment to provide solutions to problems of moderate complexity.
  • Independently analyze or design moderately complex library data sets using a variety of approaches within generally established methods, recommending improvements/processes as appropriate.
  • Respond dynamically to unique, unexpected needs in library design by using creativity with established and/or creative methods.
  • Responsible for the creation and maintenance of individual software tools for library design or analysis.

Qualifications

  • Master's degree in Biology, Engineering, Computer Science, or related fields, or the equivalent combination of education and related experience.
  • Fundamental knowledge of proteins, and bioinformatics, including some familiarity with experimental library generation, assays, sequencing, sorting, and other relevant biological domain knowledge.
  • Fundamental level skills and knowledge of concepts in data science, statistics, and machine learning.
  • Proficient programming skills in Python, including experience using in collaborative development environments and practices.
  • Fundamental knowledge and experience with appropriate software for bioinformatics and structural biology.
  • Sufficient verbal and written communication skills to collaborate effectively in a diverse team environment and present and explain technical information.
  • Previous experience working as a member of an interdisciplinary team to successfully complete objectives.
  • Ability to balance parallel threads of work.

Additional qualifications at the SES.2 level

  • Demonstrated knowledge of and prior experience working with library-scale bioinformatic data.
  • Proficient communication skills and demonstrated effectiveness in multidisciplinary settings, including a strong record of documentation of executed work.
  • Ability to prioritize, balance, and keep several parallel threads of work in simultaneous, smooth motion.

Qualifications We Desire

  • PhD in Biology, Engineering, Computer Science, or related fields, or the equivalent combination of education and related experience.
  • Advanced programming and data science skills, including advanced level programming skills in Python.
  • Strong bioinformatics programming skills, including handling and analyzing library-scale data.

Additional Information

#LI-Hybrid

Position Information

This is a Career Indefinite position, open to Lab employees and external candidates.

Why Lawrence Livermore National Laboratory?

Security Clearance

None required.  However, if your assignment is longer than 179 days cumulatively within a calendar year, you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  (This process does not apply to foreign nationals.) 

Pre-Employment Drug Test

External applicant(s) selected for this position must pass a post-offer, pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

Wireless and Medical Devices

Per the Department of Energy (DOE), Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties, you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes, but not limited to cell phones, tablets, fitness devices, wireless headphones, and other Bluetooth/wireless enabled devices.  

If you use a medical device, which pairs with a mobile device, you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

How to identify fake job advertisements

Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under “Find Your Job” of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent, we strongly recommend you do not respond.

To learn more about recruitment scams: https://www.llnl.gov/sites/www/files/2023-05/LLNL-Job-Fraud-Statement-Updated-4.26.23.pdf

Equal Employment Opportunity

We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, marital status, national origin, ancestry, sex, sexual orientation, gender identity, disability, medical condition, pregnancy, protected veteran status, age, citizenship, or any other characteristic protected by applicable laws.

We invite you to review the Equal Employment Opportunity posters which include EEO is the Law and Pay Transparency Nondiscrimination Provision.

Reasonable Accommodation

Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process, please use our online form to submit a request. 

California Privacy Notice

The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants, employees, and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.

Average salary estimate

$147786 / YEARLY (est.)
min
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$117180K
$178392K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Protein Library Design Data Scientist, LLNL

If you're passionate about merging data science with biology, then the Protein Library Design Data Scientist position at Lawrence Livermore National Laboratory (LLNL) might just be your next big adventure! Located in the scenic Livermore, CA, this role invites you to delve deep into the fascinating world of protein library design. You’ll be part of an interdisciplinary team that thrives on collaboration, creativity, and innovative solutions. In this role, you’ll focus on designing, analyzing, and disseminating data that feeds into major scientific projects. Your strong knowledge in machine learning and biological data will guide you as you contribute to library design efforts, communicate effectively with both internal and external teams, and implement efficient workflows. As a member of the Computational Engineering Division, you'll enjoy the excitement of high-impact research while working in a supportive and inclusive environment. If you have a Master's degree in relevant fields and some programming skills in Python, you’ll find this job a fantastic opportunity to grow your expertise while working towards meaningful scientific goals. Don’t miss out on the chance to play a crucial role in advancing research that truly matters!

Frequently Asked Questions (FAQs) for Protein Library Design Data Scientist Role at LLNL
What are the main responsibilities of the Protein Library Design Data Scientist at Lawrence Livermore National Laboratory?

As the Protein Library Design Data Scientist at Lawrence Livermore National Laboratory, your responsibilities include collaborating with teams to create data generation workflows, analyzing and disseminating library data, and building tools that enhance the efficiency of library design efforts. You will execute designs and work independently on more complex projects, depending on your level of expertise.

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What qualifications are needed for the Protein Library Design Data Scientist position at LLNL?

To qualify for the Protein Library Design Data Scientist role at Lawrence Livermore National Laboratory, candidates should possess a Master's degree in Biology, Engineering, Computer Science, or related fields. Fundamental knowledge of proteins, data science, and machine learning is essential along with programming skills in Python. Experience in interdisciplinary teams is highly valued.

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What is the salary range for the Protein Library Design Data Scientist role at LLNL?

The salary for the Protein Library Design Data Scientist at Lawrence Livermore National Laboratory ranges from $117,180 to $178,392 annually, depending on your specific level of experience and expertise. The final compensation will also consider various factors such as performance and geographic location.

Join Rise to see the full answer
What is the work environment like for the Protein Library Design Data Scientist at LLNL?

The work environment for the Protein Library Design Data Scientist at Lawrence Livermore National Laboratory is collaborative and inclusive. You’ll be working in a diverse team that celebrates varied perspectives and skills, ensuring a supportive atmosphere where innovative ideas flourish.

Join Rise to see the full answer
What growth opportunities exist for the Protein Library Design Data Scientist at LLNL?

At Lawrence Livermore National Laboratory, the Protein Library Design Data Scientist role offers numerous growth opportunities. You can expand your skills through participation in challenging projects, continuous learning programs, and collaborations with experts from various fields, thus enhancing both your professional and personal development.

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Common Interview Questions for Protein Library Design Data Scientist
Can you describe your experience with protein library design as a Data Scientist?

When answering this question, you should highlight specific projects where you contributed to protein library design, the methodologies you utilized, and any programming or data analysis tools you employed. Emphasizing teamwork and communication with internal or external stakeholders adds value to your response.

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What programming languages are you proficient in for data analysis in biological projects?

Indicate your proficiency in Python, detailing specific libraries or frameworks you are familiar with, such as NumPy or Pandas. It's beneficial to share examples of how you have utilized these skills in previous roles or projects to analyze biological data effectively.

Join Rise to see the full answer
How do you prioritize tasks when managing multiple projects at once?

When asked about prioritization, discuss your methods for assessing project deadlines, complexity, and importance. Share your experience with time management tools or strategies that have helped you balance and deliver quality results on parallel threads of work.

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Explain how you collaborate with interdisciplinary teams.

In responding, provide examples of past projects where you effectively collaborated with members from different fields. Highlight your communication skills and how you contributed to achieving common objectives despite varying areas of expertise.

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What statistical methods do you commonly use in data analysis?

Discuss the statistical methods that you are comfortable with, such as regression analysis or machine learning algorithms. Explain how you have applied these methods in real-world scenarios to derive meaningful insights from data.

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What challenges have you faced in data science related to biological data, and how did you overcome them?

Focus on a specific challenge from your past experiences that relates to biological data. Describe the problem, your approach to resolving it, and the outcome of your efforts, demonstrating your problem-solving skills and adaptability.

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Can you explain a complex data set you worked with and your approach to analyzing it?

Provide a detailed yet concise breakdown of a particular complex data set you have handled in your career. Discuss the methodologies employed for analysis and interpretations you were able to derive from the data, showcasing your analytical skills.

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Describe your familiarity with bioinformatics tools and software.

Detail the bioinformatics tools and software you have used, providing specific contexts where they were beneficial in your work. Mention any particular projects where these tools were crucial for success.

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What inspired you to pursue a career in protein data science?

Share your personal motivations and experiences that led to your interest in this field. Discuss any academic achievements, internships, or projects that sparked your passion for protein data science and how you envision your future in the area.

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How do you stay updated with the latest trends in data science and biology?

Indicate how you engage with current literature, attend conferences, and participate in online courses to stay abreast of trends. Providing examples of how you've implemented new knowledge into your practice would be an excellent addition to your answer.

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Established in 1952 and headquartered in Livermore, California, The Lawrence Livermore National Laboratory (LLNL) is a scientific research laboratory founded by the University of California. The laboratory is primarily funded by the United States ...

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Full-time, hybrid
DATE POSTED
January 8, 2025

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