Let’s get started
By clicking ‘Next’, I agree to the Terms of Service
and Privacy Policy
Jobs / Job page
Senior Protein Design Data Scientist image - Rise Careers
Job details

Senior Protein 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

$140,700 - $178,392 Annually for the SES.2 level
$168,780 - $214,032 Annually for the SES.3 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 Team lead or Co-lead for protein library data design, analysis, and dissemination. This role requires an interdisciplinary approach, including knowledge of data science, machine learning, and biological data. You will have a leading role in external and internal library efforts. You will provide leadership and fully-contextualized decision-making toward effective, efficient, and rapid library data generation. You will coordinate with internal and external stakeholders, including both short-term operational stakeholders and longer-term research stakeholders, particularly in machine learning; external and internal partners who perform the laboratory work to create and assay the properties of these libraries; and the data science, structural biology and other contributors who will be led in this broader effort. All of these components must be undertaken in the service of and in coordination with broader efforts. This position is 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

  • Contribute, participate, and work in coordination with partners and stakeholder teams to continue and expand:
    • the generation of library data;
    • the analysis and design of library data;
    • the dissemination of library data  
    • the development of mature, effective workflows for library design in appropriate use cases
  • Work under limited direction using independent judgment to provide solutions to problems of moderate complexity.
  • Respond dynamically to unique, unexpected needs in library design by using creativity with established and/or creative methods.
  • Perform other duties as assigned.

Additional job responsibilities, at the SES.3 level

  • Provide overall technical leadership and guidance and serve as primary point of contact for library design.
  • Provide solutions to complex problems using in-depth analysis and collaborate in the development of innovative methods/technology.
  • Contribute to the definition and articulation of strategy for library data in the context of wider LLNL efforts to generate effective predictors for protein properties.

Qualifications

  • PhD in Biology, Engineering, Computer Science, or related fields, or the equivalent combination of education and related experience.
  • Comprehensive knowledge of, and previous experience with conversancy of proteins, protein structure, bioinformatics, experimental library generation, assays, sequencing, sorting, and other relevant biological domain knowledge.
  • Comprehensive knowledge of, and previous experience with with data science, statistics, and machine learning.
  • Programming skills in  Python including experience with collaborative development environments and practices.
  • Knowledge of appropriate software for bioinformatics and structural biology.
  • 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.

Additional qualifications at the SES.3 level:

  • Significant experience leading interdisciplinary teams,  including setting clear expectations, delegating to subordinates and peers, and ensuring successful, timely completion of objectives.
  • Demonstrated ability and experience managing many parallel threads of work in simultaneous, smooth motion, in coordination with and leading a team of several employees.
  • Ability to engage and negotiate with stakeholder input; dynamically reprioritize in response to resulting decisions.
  • Advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.

Qualifications We Desire

  • Advanced level programming and data science skills, including demonstrated strong programming skills in Python.
  • Knowledge of DNA synthesis techniques, library design, assembly, and deep sequencing.
  • Advanced level knowledge of and previous experience with advanced protein machine learning techniques, such as AlphaFold, ESM, and RFDiffusion.
  • Strong understanding of fundamental statistical and machine learning principles that underpin successful training of models with effective generalization capabilities, as well as experimental design..
  • Strong understanding of the current state of the field of computational protein design, as well as the strategic implications of this understanding on LLNL efforts.

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

$177366 / YEARLY (est.)
min
max
$140700K
$214032K

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 Senior Protein Design Data Scientist, LLNL

At Lawrence Livermore National Laboratory (LLNL), we’re on a mission to harness cutting-edge science and technology to create meaningful solutions, and we want you to be a part of it! We’re looking for a Senior Protein Design Data Scientist to join our dynamic team in Livermore, CA. In this pivotal role, you’ll lead the charge on protein library data design, analysis, and dissemination, integrating your unique blend of data science and biology to push the boundaries of what’s possible in protein research. You’ll work closely with internal and external partners, guiding interdisciplinary teams to generate, analyze, and share vital library data. Your expertise in machine learning and biological data will empower you to respond creatively to both predictable and unforeseen challenges in library design. Whether it's using Python for programming, leading technical discussions, or managing multiple threads of innovative research, your contributions will be essential to our broader mission at LLNL. Your leadership skills will shine as you provide technical guidance and collaborate with stakeholders to drive projects forward. We’re excited about the future you can help us build—a future characterized by innovation, inclusivity, and groundbreaking scientific achievement. Join us at LLNL, where every day is an opportunity for tremendous progress and meaningful impact!

Frequently Asked Questions (FAQs) for Senior Protein Design Data Scientist Role at LLNL
What qualifications do I need for the Senior Protein Design Data Scientist role at Lawrence Livermore National Laboratory?

To excel as a Senior Protein Design Data Scientist at Lawrence Livermore National Laboratory, you should ideally hold a PhD in Biology, Engineering, Computer Science, or a related field. It’s important to have comprehensive knowledge regarding protein structures and bioinformatics, along with experience in machine learning and data sciences. Proficiency in Python programming and familiarity with software for bioinformatics is also crucial to succeed in this role.

Join Rise to see the full answer
What are the main responsibilities of a Senior Protein Design Data Scientist at LLNL?

As a Senior Protein Design Data Scientist at LLNL, your primary responsibilities include leading the design, analysis, and dissemination of protein library data. You will engage with both internal and external stakeholders, provide technical leadership, and collaborate with teams to create innovative workflows. You’ll also be expected to contribute to problem-solving and dynamically address unexpected needs in library design using your deep knowledge of the field.

Join Rise to see the full answer
What kind of work environment can I expect at Lawrence Livermore National Laboratory as a Senior Protein Design Data Scientist?

At LLNL, you can look forward to a collaborative and inclusive work environment where diverse ideas are celebrated. The culture emphasizes teamwork across various disciplines and encourages innovation. You’ll have the freedom to pursue impactful scientific research alongside some of the brightest minds, contributing to projects that have significant implications for national security and scientific advancement.

Join Rise to see the full answer
What are the salary expectations for the Senior Protein Design Data Scientist position at LLNL?

The salary range for the Senior Protein Design Data Scientist role at Lawrence Livermore National Laboratory varies between $140,700 to $214,032 annually, depending on the level of experience and expertise you bring to the role. This competitive pay reflects the value placed on the skills and qualifications needed to drive impactful research and development at LLNL.

Join Rise to see the full answer
What additional skills are desirable for the Senior Protein Design Data Scientist position at LLNL?

In addition to the core responsibilities, desirable skills for the Senior Protein Design Data Scientist role at LLNL include advanced programming capabilities in Python, knowledge of DNA synthesis techniques, and familiarity with machine learning models specifically related to protein design. Understanding current computational protein design trends and their strategic implications can also significantly enhance your candidacy.

Join Rise to see the full answer
Common Interview Questions for Senior Protein Design Data Scientist
How do you approach protein data analysis and what tools do you typically use?

In conducting protein data analysis, I typically employ a combination of programming in Python and bioinformatics software tools. My approach includes cleaning and preparing the dataset, followed by deploying various statistical methods and machine learning algorithms to extract relevant insights. Clear documentation of each step helps ensure transparency and reproducibility, which is essential for collaborative environments like LLNL.

Join Rise to see the full answer
Can you describe a challenging project you led and how you overcame obstacles?

I once led a project where we were tasked with designing a novel protein library under tight deadlines. The main challenge was a lack of existing data for comparative analysis. To tackle this, I encouraged creative brainstorming sessions among team members and initiated partnerships with external stakeholders. By pooling resources and expertise, we successfully established new methods for generating synthesis data and achieved our project goals on time.

Join Rise to see the full answer
What strategies do you use to manage multiple projects simultaneously?

I prioritize effective project management by using tools like Gantt charts to visualize timelines and deliverables while setting clear milestones for each project. I also conduct regular check-ins with team members to align on progress and adjust priorities as needed. This structured yet flexible approach allows me to balance competing demands while ensuring quality outcomes.

Join Rise to see the full answer
How do you ensure effective communication with interdisciplinary teams?

I prioritize building rapport and establishing clear channels of communication across disciplines. I make it a point to understand the specific jargon and concerns of different teams and encourage open dialogue. Regular meetings, collaborative writing platforms, and documentation serve to ensure everyone stays informed and engaged in the project’s progress and goals.

Join Rise to see the full answer
Give an example of how you've used machine learning in a previous project.

In a recent project focused on predicting protein structure, I utilized machine learning algorithms to analyze large datasets of protein sequences. By implementing techniques like supervised learning and using tools such as TensorFlow, I trained the model to improve its predictive accuracy, which ultimately enhanced our understanding of structure-function relationships in proteins.

Join Rise to see the full answer
What is your experience with protein library generation techniques?

My experience with protein library generation includes applying methods such as combinatorial synthesis and high-throughput screening. I've worked on developing streamlined workflows that integrate experimental data directly into computational models, facilitating rapid iterations in the design process while ensuring the libraries are relevant and impactful.

Join Rise to see the full answer
How would you define success in protein design at LLNL?

Success in protein design at LLNL can be defined as the ability to translate scientific insights into tangible applications that meet national security needs. It involves understanding evolving challenges in the field, collaborating effectively with others, and being the catalyst for innovative breakthroughs that push the boundaries of our current capabilities.

Join Rise to see the full answer
What role does collaboration play in your work style as a Senior Protein Design Data Scientist?

Collaboration is at the core of my work style. I believe that diverse perspectives lead to more innovative solutions. In every project, I make it a priority to engage with colleagues from different domains early on, ensuring we’re all aligned on objectives. This fosters a creative environment where sharing ideas and feedback is encouraged and helps drive the success of our projects.

Join Rise to see the full answer
How do you keep up with the latest advancements in computational protein design?

To stay abreast of developments in computational protein design, I regularly read relevant scientific journals, participate in online webinars, and attend industry conferences. Engaging with professional networks and communities of practice also provides valuable insights from peers and experts. Continuous learning is key to maintaining relevance and enhancing my contributions.

Join Rise to see the full answer
Describe your experience in documenting research and findings. How do you ensure clarity?

My experience in documenting research encompasses writing clear, structured reports and creating informative presentations. I follow a systematic approach that includes outlining key findings, presenting data visually, and reflecting on potential implications or next steps. I always seek peer feedback to enhance clarity and effectiveness, ensuring that my documentation can be easily understood by varied audiences.

Join Rise to see the full answer
Similar Jobs
Photo of the Rise User
LLNL Remote Livermore, CA, USA
Posted 2 days ago
Photo of the Rise User
LLNL Remote Livermore, CA, USA
Posted 2 days ago
Photo of the Rise User
AECOM Remote West Palm Beach, FL, United States
Posted 14 days ago
Photo of the Rise User
DeepMind Hybrid Mountain View, California, US
Posted 6 days ago
Photo of the Rise User
Electra Hybrid Boulder, Colorado, United States
Posted 6 days ago
Photo of the Rise User
EcoVadis Remote Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
Posted 5 days ago
Photo of the Rise User
Posted 4 days ago

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 ...

45 jobs
MATCH
Calculating your matching score...
FUNDING
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
January 7, 2025

Subscribe to Rise newsletter

Risa star 🔮 Hi, I'm Risa! Your AI
Career Copilot
Want to see a list of jobs tailored to
you, just ask me below!