Senior Research Scientist, Predictive Modeling and AI Insights

Flatiron Health; London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A healthcare technology company in London seeks a Senior Research Scientist to develop AI/ML solutions in oncology. The role involves collaborating with multidisciplinary teams to create predictive models and generate insights from real-world data. Ideal candidates will have a PhD or Master's in quantitative fields and experience in healthcare predictive modeling. This position offers a competitive salary and a range of benefits.

Benefits

Annual bonus

Equity options

Full medical benefits

Qualifications

• 3-4 years of relevant experience or 6-8 years with Master's.
• 4+ years building predictive models for healthcare.
• Experience with deep learning techniques.

Responsibilities

• Drive design of AI/ML solutions for pharma.
• Prototype advanced analytic solutions.
• Generate comprehensive reports on model performance.

Skills

AI/ML solution development

Collaborative problem-solving

Data analysis

Education

PhD in machine learning, data science, statistics

Master's degree in related fields

Tools

R

Python

Job description

Senior Research Scientist, Predictive Modeling and AI Insights

NY hub or London office

Reimagine the infrastructure of cancer care within a community that values integrity, inspires growth, and is uniquely positioned to create a more modern, connected oncology ecosystem.

We’re looking for a senior research scientist to help us accomplish our mission to improve and extend lives by learning from the experience of every person with cancer. Are you ready to be the next changemaker in cancer care?

What You’ll Do

In this role, you will work as a member of the Research Sciences (RS) department using Artificial Intelligence (AI)/Machine Learning (ML) that will transform oncology drug development and clinical practice. You will work with a cross-functional team with clinical, data and domain expertise to develop new applications of AI/ML with Flatiron multi-modal real world data to generate insights and evidence. This can include projects such as digital twins, predictive modeling, and more. Specifically, you will:

• Drive the design and development of innovative AI/ML solutions for pharma use cases impacting drug development and patient care
• Design and prototype advanced analytic and machine learning solutions leveraging multimodal real world data (RWD)
• Generate comprehensive reports detailing model training, performance and extracted insights, and effectively communicate findings and recommendations to the study teams and clients
• Lead preparations and authorship of abstracts, manuscripts and publications related to predictive modeling projects
• Work collaboratively with multidisciplinary teams such as project managers, clinicians and other stakeholders to design, execute and deliver on client-sponsored predictive modeling studies in an accurate, effective, and timely manner
• Advance the methodologies and applications of real-world data and AI/ML to shape the future of insights and evidence generation for the life sciences sector

Who You Are

You're a kind, passionate and collaborative problem-solver. In addition, you’re an analytical thinker and excellent communicator with experience developing AI/ML solutions using multi-modal real-world data. You are excited by the prospect of rolling up your sleeves to tackle meaningful problems each and every day.

• You hold a PhD degree in quantitative field such as machine learning, data science, statistics/biostatistics or applied mathematics with 3 - 4 years of relevant experience (can include work experience before graduate school) or a Master’s degree in one of these fields with 6 - 8 years of relevant experience
• You have 4+ years of hands on experience building predictive models for real world healthcare and drug development use cases
• You are proficient with advanced machine learning techniques including deep learning approaches (e.g. neural networks, variational autoencoders, generative adversarial networks) and causalML methods
• You have a strong knowledge of time to event analysis methods and other epidemiological methods commonly used in retrospective real world evidence generation
• You love working with data and have experience exploring it with a critical and thoughtful eye
• You are proficient in open source data science tools and language (R and Python)
• You have strong organizational, time-management, prioritization and decision-making skills necessary to evaluate, plan and implement multiple high-visibility projects in a timely fashion
• You have experience collaborating with researchers in the life science industry, academia, or government agencies to design and deliver high-quality studies that meet their needs
• You know how to balance attention to detail with execution against tight timelines
• You have the ability to work effectively in a constantly changing, diverse, and matrix environment
• You are able to quickly learn and apply new information, skills and procedures
• You are passionate about our mission to improve healthcare through technology

Extra Credit

• You have oncology experience, particularly predicting cancer outcomes
• You have healthcare consulting experience
• You have experience working with longitudinal EMR data

Job Compensation Range

Salary Range:

Preferred Primary Location:

NY hub

An important note on compensation

The pay range for this position is based on the preferred primary location of the role which is listed above. If you are applying to this role at a location that is not the preferred primary location, please keep in mind the salary range will vary and may fall outside of what is listed. Base pay offered may vary depending on job-related knowledge, skills, and experience. An annual bonus and equity may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, depending on the position offered.

Flatiron Health is proud to be an Equal Employment Opportunity employer.

We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.