Senior Data Science Engineer

Senior Data Science Engineer (Hybrid)

*Visa Sponsorship is not available for this position.

About the Center for Avian Population Studies

The Center for Avian Population Studies (CAPS) at the Lab is dedicated to enhancing biodiversity data resources to support conservation and scientific research. Central to CAPS, the eBird Status and Trends (S&T) project leverages innovative analytical methods to translate eBird’s global participatory science bird observations into standardized, scalable, cutting-edge scientific, computational data resources. Within CAPS, the Conservation Science Program is focused on translating S&T data resources into innovative approaches for how we understand and protect biodiversity, filling spatial and temporal data gaps and controlling for biases through advanced models. The freely available data products in CAPS empower researchers, conservationists, NGOs, and government agencies worldwide, advancing ecological insights, enabling evidence-based conservation planning, and redefining our approach to protecting the natural world. In 2024, these resources were downloaded more than 1 million times.

The Opportunity

While position responsibilities vary, all people leaders are expected to foster a culture of belonging and a psychologically healthy work environment by being trustworthy; respecting all individuals; being flexible; supporting work/life integration as well as healthy boundaries; inviting new ideas, alternatives, and perspectives; speaking up and taking action if others are being excluded or treated inappropriately; and recognizing the contributions of others. 

CAPS seeks a visionary computer science engineer who is excited to lead the development of artificial intelligence and machine learning approaches to real-world challenges and science-to-action needs that advance the strategic objectives of CAPS and the Lab. The desired candidate is a critical thinker who thrives working with an interdisciplinary team of ecologists, conservation scientists, engineers, and domain experts.

The Senior Data Science Engineer will lead the research, development, and scaling of Artificial Intelligence/Machine Learning/Deep Learning (AI/ML/DL) using eBird data across all programs in CAPS and the Lab. This role will build on the success and experience of the existing team at developing a global workflow for high spatiotemporal resolution avian distributions and population trends, and for applying these to real world problems. The role will significantly expand the analysis capabilities of CAPS into joint species distribution models including the integration of new data modalities to leverage Lab data streams, expanding our geographic and taxonomic coverage, and developing novel approaches to strengthen inference for critical conservation planning and decision-making applications.

The Senior Data Science Engineer will 1) lead research in AI/ML/DL, and related fields to identify, adapt, develop and scale methods to improve existing S&T analysis and data products, 2) collaborate in publishing findings in peer-reviewed conferences and journals and leading the engagement of CAPS with the AI/ML/DL and ecological research communities, 3) lead the development of new methods and data products that meet CAPS strategic objectives, including the testing and validation of prototypes, 4) lead research and testing that allows the transition of prototypes to production versions in collaboration with CAPS production team, CLO software engineers and external partners, 5) lead collaborations in AI/ML/DL across all CAPS science and production teams to advance important scientific and conservation applications of eBird analytical methods, tools, and data products. The Senior Data Science Engineer will be the technical lead for AI/ML/DL for all of CAPS and will develop and direct a professional team that includes research engineers and domain experts. This position will also lead collaborations in AI/ML/DL with similar positions in other Centers across the Cornell Lab and lead collaborations and knowledge transfer with the Institute for Computational Sustainability at Cornell University including the mentoring and supervision of graduate and postdoctoral students. 

What We Need

Required Qualifications:

• Bachelor’s degree in in computer science or related field with a focus in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and optimization or related sub areas of machine learning.
• At least five (5) years of experience in AI/ML/DL or equivalent combination of education and experience.
• Demonstrated experience in algorithm development and structured programming ability. Experience in scientific programming and the generation of highly complex code