At a Glance
- Tasks: Analyse large datasets to uncover insights about brain aging and neurodegeneration.
- Company: Join Stanford University, a leader in neuroscience research and innovation.
- Benefits: Enjoy competitive pay, career development, health benefits, and a vibrant campus culture.
- Why this job: Make a real impact on brain health while working with top researchers in the field.
- Qualifications: PhD or Master’s in a relevant field, strong programming skills, and data analysis experience.
- Other info: Dynamic work environment with opportunities for growth and collaboration.
The predicted salary is between 60000 - 80000 ÂŁ per year.
Anchored in the Wu Tsai Neurosciences Institute and the Office of the Dean of Research, the Knight Initiative in Brain Resilience is a cross‑disciplinary scientific endeavor aimed at addressing neurodegeneration, aging and brain resilience. Diseases and associated issues of cognitive decline like Alzheimer's, Parkinson's, dementia and related ailments are increasing with our rapidly aging global population. Stanford seeks to advance a new era of brain science focused on accelerating the fundamental understanding of the aging brain, both the biological causes of neurodegeneration and how to increase brain resilience throughout the lifespan.
We are seeking a highly skilled and experienced Data Scientist to join our team. The successful candidate will be responsible for managing and analyzing large sets of multi‑omics data with a focus on human brain aging. They will work closely with the research team to identify patterns and correlations in the data related to brain aging, develop and implement data analysis pipelines and workflows, generate visualizations and reports, and contribute to the development of predictive models and algorithms. The Data Scientist will be responsible for developing and adapting data collection and analysis methods, identifying and resolving data quality issues, and collaborating with various stakeholders.
Core Duties
- Collect, manage and clean datasets.
- Manage and analyze large sets of data from various sources, including genomics, transcriptomics, proteomics, and metabolomics.
- Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data.
- Utilize and fine‑tune genomic foundation models on aging data.
- Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.
- Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.
- Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.
- Analyze data processes in documentation.
- Collaborate with faculty and research staff on data collection and analysis methods.
- Provide documentation based on audit and reporting criteria to investigators and research staff.
- Communicate with government officials, grant agencies and industry representatives.
Education & Experience
- Bachelor’s degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.
Knowledge, Skills and Abilities
- Substantial experience with MS Office and analytical programs.
- Strong writing and analytical skills.
- Excellent communication and presentation skills.
- Ability to prioritize workload.
Preferred Qualifications
- PhD or Master’s degree in a relevant field such as data science, bioinformatics, computational biology or statistics.
- Strong programming skills, including experience with R or Python.
- Experience with multi‑omics data analysis and/or experience with brain aging research.
- Strong understanding of statistical methods and machine learning techniques.
- Experience with building genomics foundation models, using HPC and cloud computing platforms such as AWS or Azure is a plus.
Physical Requirements
- Frequently grasp lightly/fine manipulation, perform desk‑based computer tasks, lift/carry/push/pull objects that weigh up to 10 pounds.
- Occasionally stand/walk, sit, twist/bend/stoop/squat, grasp forcefully.
- Rarely kneel/crawl, climb (ladders, scaffolds, or other).
Working Conditions
- May work extended or non‑standard hours based on project or business needs. Occasional local travel may be required.
- Some work may be performed in a laboratory setting.
- May be exposed to allergens/biohazards/chemicals, confined spaces, unusual work hours or routine overtime and/or inclement weather.
Work Standards
- Interpersonal skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote culture of safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide.
Pay
The expected pay range for this position is $80,148 to $99,773 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on a wide range of factors that are unique to each candidate including but not limited to geographic location, knowledge, skills and abilities, relevant education, depth and breadth of experience, performance; as well as other business and organization needs.
Benefits
At Stanford University, base pay represents only one aspect of the comprehensive rewards package. The Cardinal at Work website provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees.
Why Stanford Is For You
Imagine a world without search engines or social platforms. Consider lives saved through first‑ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy.
Data Scientist employer: Stanford University
Contact Detail:
Stanford University Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the neuroscience and data science fields. Attend events, join online forums, or even slide into LinkedIn DMs. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those related to brain aging or multi-omics data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Be ready to explain complex data concepts in simple terms. Remember, they want to see how well you can collaborate with researchers and faculty, so practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at Stanford. So, hit that apply button!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight relevant experience, especially in data analysis and multi-omics data management. We want to see how your skills align with our mission at Stanford!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about brain resilience and how your background makes you a perfect fit for our team. Let us know what excites you about this opportunity!
Showcase Your Technical Skills: Don’t forget to mention your programming skills, especially in R or Python, and any experience with machine learning techniques. We’re keen on seeing how you can contribute to our data analysis pipelines!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows you’re serious about joining our amazing team at Stanford!
How to prepare for a job interview at Stanford University
✨Know Your Data Inside Out
Before the interview, dive deep into the types of multi-omics data you'll be working with. Familiarise yourself with genomics, transcriptomics, proteomics, and metabolomics. Being able to discuss specific examples of how you've managed and analysed these datasets will show your expertise and readiness for the role.
✨Show Off Your Programming Skills
Make sure you brush up on your programming skills, especially in R or Python. Be prepared to discuss any projects where you've used these languages to develop algorithms or statistical models. If you can share a relevant project or two, that’ll definitely impress the interviewers!
✨Communicate Clearly and Confidently
Since excellent communication is key for this role, practice explaining complex data concepts in simple terms. Think about how you would present your findings to non-technical stakeholders. This will demonstrate your ability to collaborate effectively with faculty and research staff.
✨Prepare Questions About the Research
Show your genuine interest in the Knight Initiative in Brain Resilience by preparing thoughtful questions about their current research projects. Ask about their methodologies or any challenges they face in data analysis. This not only shows your enthusiasm but also your proactive approach to understanding their work.