Senior Data Scientist, Patient Data in Epidemiology and Patient Data Products

About Us

Valo Health is a human-centric, AI-enabled biotechnology company working to make new drugs for patients faster. The company's Opal Computational Platform transforms drug discovery and development through a unique combination of real-world data, AI, human translational models and predictive chemistry.

Our talented team of biologists, chemists and engineers, armed with advanced AI/ML tools, work together to break down traditional R&D silos and accelerate the speed and scale of drug discovery and development.

Valo is committed to hiring diverse talent, prioritizing growth and development, fostering an inclusive environment, and creating opportunities to bring together a group of different experiences, backgrounds, and voices to work together. We embrace new ways of learning, solve complex problems and welcome diverse perspectives that can help us advance patient-centric innovation.

Valo is headquartered in Lexington, MA, with additional offices in New York, NY and Tel Aviv, Israel. To learn more, visit www.valohealth.com. 

About the Role

As a Senior Patient Data Expert in Epidemiology and Patient Data Products, reporting to the head of IL office, you will be a core member of a team of epidemiologists, data scientists, and data engineers building a powerful computational platform for advancing the discovery and development of new medicines. In this role, you will curate data and answer research questions using large real world healthcare databases under the guidance of drug discovery program leads. To do so, you will work in partnership with colleagues in clinical data informatics, data engineering, and machine learning to develop solutions to challenging computational problems. Successful candidates will work with a diverse set of scientists and domain experts, in ways that cut across traditional industry boundaries in an innovative startup environment.

What You'll Do...

• Be Valo patient data expert, develop a deep understanding of Valo patient data, spanning structured and unstructured electronic medical records and biobank registries, and its applications in drug discovery research.
• Use your technical expertise and problem-solving skills to articulate and break down large problems into solvable pieces. There are a lot of problems to solve; you'll need to prioritize which of these are critical-path today from those that can wait to maximize impact.
• Work closely with clinical informatics, clinical data engineers, and machine learning teams across global sites to optimize patient data utilization, and ensure high quality datasets for research and development
• Be a dynamic and active team member, writing high-quality, reproducible analysis code in R and Python, participating in code review, and providing regular updates of your work and contribute to the work of your colleagues.
• Design comprehensive data curation strategies, leveraging AI and machine learning tools, execute and conduct patient data validation studies, and prioritize efforts based on scientific leadership input and customer needs.
• Create detailed reports that summarize findings and provide actionable recommendations that support internal data science and engineering teams in improving Valo's patient data assets and advancing real-world data initiatives.
• Be comfortable with scientific uncertainty and embrace curiosity and creative solutions. Many of the challenges we're trying to address don't have known solutions or clear processes to arrive at answers.
  
  

• MPH, MS in public health, epidemiology, biostatistics, applied statistics or related quantitative field with 5+ years of experience working with real-world health data.
• High proficiency in Hebrew and English, with the ability to communicate effectively in both languages in a professional setting.
• Demonstrated ability to execute robust analytical strategies using healthcare databases including structured and unstructured electronic health records, administrative claims databases, and/or patient registries.
• Hands on experience in population health observation studies, including designing survey or medical chart abstraction instruments, curating patient data and constructing relational databases.
• Experience with epidemiology research methods including cohort and case-control study design, and interpreting inferential statistical outputs.
• Must have experience conducting data manipulation, statistical analysis and visualization in Python and/or R programming languages.
• Experience developing research proposals and conducting feasibility studies.
• Comfortable working in ambiguous problem spaces; experience working in a start-up or agile work environment as part of cross-functional project teams.
• Exceptional time management, ability to prioritize multiple tasks simultaneously, and deliver products on time.
  
  

• Experience working in Israeli electronic medical records is a plus.
• Advanced knowledge in biostatistics approaches, including inferential modeling, predictive modeling, and implementing unsupervised machine learning algorithms in real world health care databases is a plus.
• Experience translating machine learning output into meaningful insights for diverse audiences is a plus.
• Familiarity with or exposure to traditional drug discovery and development processes and approaches is a plus.
• Familiarity with integrated clinico–omics datasets (including sequencing, genomics, proteomics, etc) is a plus.