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Let’s say you work for a social media company that has just done a launch in a new city. Looking at weekly metrics, you see a slow decrease in the average number of comments per user from January to March in this city.

The company has been consistently growing new users in the city from January to March.

What are some reasons why the average number of comments per user would be decreasing and what metrics would you look into?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

Decreasing Comments

How would you investigate a decline in the average number of comments per user?

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Experiment Validity

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

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At Caris, we understand that cancer is an ugly word—a word no one wants to hear, but one that connects us all. That’s why we’re not just transforming cancer care—we’re changing lives.

We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day:  “What would I do if this patient were my mom?”  That question drives everything we do.

But our mission doesn’t stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare—driven by innovation, compassion, and purpose.

Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.

Position Summary

Caris Life Sciences is looking for a seasoned, innovative, and impact-driven Senior Data Scientist for R&D to enable and expand the Caris suite of histopathology biomarkers. This role will be responsible for leading the development of computer vision-based machine learning algorithms and analytic pipelines to drive Caris' research initiatives forward, including guiding the design, development, and maintenance of the machine learning infrastructure. The successful candidate will possess deep analytical expertise, demonstrated leadership, strong communication skills, and a passion for personalized medicine and innovation. In addition, the position has numerous opportunities for publishing scientific results and mentoring junior team members.

Job Responsibilities

Design, implement, refine, and test algorithms and workflows to support strategic goals in image biomarker discovery, molecular profiling, and translational R&D.
Collaborate with pathologists and scientists to develop ground truth datasets and diverse feature sets from whole slide images (WSIs) and other modalities.
Build predictive models using both structured and unstructured data, integrating imaging, molecular, and clinical data.
Process and analyze large, multi-source datasets across various data types.
Lead cross-functional research initiatives and contribute to scientific strategy and roadmap planning.
Support ad hoc analysis and reporting requests with timely, accurate, and interpretable results.
Follow best practices in code development, documentation, and model delivery within a collaborative team setting.
Review and provide guidance on modeling approaches, experimental design, and code quality across the team.

Required Qualifications

PhD in Data Science, Computational Biology, Computer Science, Engineering, Mathematics, or a related field with demonstrated exposure to cancer biology.
At least three years experience.
Strong understanding of biological and pathology-driven questions, with the ability to develop statistical and machine learning solutions.
Proficiency in at least one general-purpose programming language (e.g., Python, Java, C++), with a preference for Python.
Experience in Linux environments and version control systems like Git.
Ability to query and manipulate both relational (SQL) and non-relational (NoSQL) databases.
Practical experience with machine learning/deep learning frameworks such as PyTorch, TensorFlow, Keras, or OpenCV.
Hands-on experience with classification, segmentation, and object detection tasks.
Familiarity with end-to-end data science workflows, including model development, validation, and deployment.
Strong written and verbal communication skills.
Demonstrated ability to lead projects, mentor junior scientists, and collaborate across multidisciplinary teams.

Preferred Qualifications

Experience working with medical imaging data, especially histopathology images from whole slide scanners.
Experience in cancer research or oncology-focused AI applications.
Prior work involving integration of imaging, molecular, and clinical datasets in multimodal modeling.
Experience with cloud computing environments (e.g., AWS, Azure, GCP) and distributed training workflows.
Hands-on experience in developing or fine-tuning foundation models for medical or pathology applications is a strong plus.

Physical Demands

Will work at a computer most of the time, with some time spent collaborating with subject matter experts and business group leaders either in person or through remote conferencing.

Training

All job-specific, safety, and compliance training are assigned based on the job functions associated with this employee.

Other

Job may require after-hours response to emergency issues.

Conditions of Employment:  Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check ( applicable for certain positions) and reference verification.

This job description reflects management’s assignment of essential functions. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time.

Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.
Seniority level    Seniority level Mid-Senior level
Employment type    Employment type Full-time
Job function    Job function Engineering and Information Technology
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At Caris, we understand that cancer is an ugly word-a word no one wants to hear, but one that connects us all. That's why we're not just transforming cancer care-we're changing lives. We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day: "What would I do if this patient were my mom?" That question drives everything we do. But our mission doesn't stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare-driven by innovation, compassion, and purpose. Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins. Position Summary Caris Life Sciences is looking for a seasoned, innovative, and impact-driven Senior Data Scientist for R&D to enable and expand the Caris suite of histopathology biomarkers. This role will be responsible for leading the development of computer vision-based machine learning algorithms and analytic pipelines to drive Caris' research initiatives forward, including guiding the design, development, and maintenance of the machine learning infrastructure. The successful candidate will possess deep analytical expertise, demonstrated leadership, strong communication skills, and a passion for personalized medicine and innovation. In addition, the position has numerous opportunities for publishing scientific results and mentoring junior team members. Job Responsibilities <ul><li>Design, implement, refine, and test algorithms and workflows to support strategic goals in image biomarker discovery, molecular profiling, and translational R&D.</li><li>Collaborate with pathologists and scientists to develop ground truth datasets and diverse feature sets from whole slide images (WSIs) and other modalities.</li><li>Build predictive models using both structured and unstructured data, integrating imaging, molecular, and clinical data.</li><li>Process and analyze large, multi-source datasets across various data types.</li><li>Lead cross-functional research initiatives and contribute to scientific strategy and roadmap planning.</li><li>Support ad hoc analysis and reporting requests with timely, accurate, and interpretable results.</li><li>Follow best practices in code development, documentation, and model delivery within a collaborative team setting.</li><li>Review and provide guidance on modeling approaches, experimental design, and code quality across the team.</li></ul> Required Qualifications <ul><li>PhD in Data Science, Computational Biology, Computer Science, Engineering, Mathematics, or a related field with demonstrated exposure to cancer biology.</li><li>At least three years experience.</li><li>Strong understanding of biological and pathology-driven questions, with the ability to develop statistical and machine learning solutions.</li><li>Proficiency in at least one general-purpose programming language (e.g., Python, Java, C++), with a preference for Python.</li><li>Experience in Linux environments and version control systems like Git.</li><li>Ability to query and manipulate both relational (SQL) and non-relational (NoSQL) databases.</li><li>Practical experience with machine learning/deep learning frameworks such as PyTorch, TensorFlow, Keras, or OpenCV.</li><li>Hands-on experience with classification, segmentation, and object detection tasks.</li><li>Familiarity with end-to-end data science workflows, including model development, validation, and deployment.</li><li>Strong written and verbal communication skills.</li><li>Demonstrated ability to lead projects, mentor junior scientists, and collaborate across multidisciplinary teams.</li></ul> Preferred Qualifications <ul><li>Experience working with medical imaging data, especially histopathology images from whole slide scanners.</li><li>Experience in cancer research or oncology-focused AI applications.</li><li>Prior work involving integration of imaging, molecular, and clinical datasets in multimodal modeling.</li><li>Experience with cloud computing environments (e.g., AWS, Azure, GCP) and distributed training workflows.</li><li>Hands-on experience in developing or fine-tuning foundation models for medical or pathology applications is a strong plus.</li></ul> Physical Demands <ul><li>Will work at a computer most of the time, with some time spent collaborating with subject matter experts and business group leaders either in person or through remote conferencing.</li></ul> Training <ul><li>All job-specific, safety, and compliance training are assigned based on the job functions associated with this employee.</li></ul> Other <ul><li>Job may require after-hours response to emergency issues.</li></ul> Conditions of Employment: Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check ( applicable for certain positions) and reference verification. This job description reflects management's assignment of essential functions. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities to this job at any time. Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.

Caris Life Sciences Interview Questions

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