Data Science Group Leader - Medical Imaging (Pathology

MIN: $160,500 MID: $203,000 MAX: $245,500

The ideal candidate will have 2 years of computational pathology experience.

The University of Texas MD Anderson Cancer Center (MDACC) is the #1 cancer center in the U.S. and a leader in cancer research and innovation through our devotion to improving the care of cancer patients. This commitment is brought to life in the Institute for Data Science in Oncology (IDSO), a flagship program designed to reshape patient experiences and fast-track scientific breakthroughs via data-driven cancer care methodologies.

The IDSO embodies a data-centric culture, pushing the envelope of modern care and venturing into uncharted territories of cancer research and treatment. It is home to a vibrant team of data scientists committed to unraveling complex cancer challenges, reducing time between diagnosis and treatment decisions, and accelerating drug discovery.

MDACC is recruiting Data Scientists for its newly established Computational Pathology program. This program aims to distil meaningful insights from the extensive resources and data available at MD Anderson, particularly from cancer pathology that is currently benefiting from a digital revolution. Automated, unbiased sample selection and scalable study design will immediately facilitate deep spatial investigations in landmark MD Anderson programs, including APOLLO and Patient MOSAIC, to direct novel data analysis, enable translational studies, and generate clinical impact.

MDACC provides the ideal environment for developing, testing, and deploying AI technologies for improved early cancer diagnosis and accurate treatment selection. The Computational Pathology program is a key focus area of the IDSO and supports the IDSO’s mission to drive high-impact discovery research by optimizing multidimensional data integration, analysis, and application.

We seek a senior level data scientist to manage the daily operations and design and development of the computational methodologies, techniques, etc. for advanced research and development in numerical analysis, mathematical modeling and data processing techniques for this program. They will lead a team of data scientists to develop cutting edge artificial intelligence (AI) and image processing methods for digital pathology, and to conduct clinical evaluation studies for implementation of these AI tools in the pathology clinical work flow.

Work Schedule and location:
Monday - Friday / 8am - 5pm / Onsite 2- 3 days - based on business needs. (Must live in Texas)

By our words and actions we demonstrate caring toward everyone.

• We are sensitive to the concerns of our patients, their loved ones and our colleagues.
• We are respectful and courteous to each other and practice cultural humility.
• We promote and reward teamwork and inclusion.

We work together with professionalism to merit the trust of our colleagues and those we serve in all that we do.

• We hold ourselves, and each other, accountable for our work – decisions and data – and for practicing our values and ethics.
• We advocate for diversity and equity for our workforce, for those we serve and for our community.
• We communicate frequently, honestly, openly and responsibly.

We embrace creativity and seek new knowledge from diverse perspectives.

• We encourage continuous learning, seeking out information and new ideas.
• We team with each other to identify and resolve problems.
• We seek personal growth and enable others to do so.

We provide a safe environment – physically and psychologically – for our patients, for our colleagues and for our community.

• We create a sense of security and empowerment and are committed to keeping one another free from harm.
• We embrace a framework and best practices for the highest quality of care and service.
• We inspire trust by modeling excellence in our work and acceptance of each person’s contributions.

We protect and preserve our institutional reputation and the precious resources – people, time, financial and environmental – entrusted to us.

We prioritize the health and well-being of each other.

We act responsibly to safeguard the institution’s finances.

We ensure…