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 eBirds 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:

• Bachelors 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 in Python R and C.
• Proven ability to develop AI tools for challenging large-scale spatiotemporal applications for both predictive and inferential objectives.
• Demonstrated experience with large-scale multi-objective Pareto optimization especially in sustainability applications.
• Ability to conduct collaborative research from conception to completion.
• Demonstrated record of collaborating with teams on scientific publications in leading peer-reviewed conferences and/or journals.
• Proven experience in leading the integration of large-scale multi-layered research projects into a production engineering system.
• Proven experience in leading the development and implementation of technical requirements specifications and documentations for data processing systems through the application of engineering and scientific procedures.
• Excellent oral and written communication skills.
• Demonstrated ability to improve performance of a team through productive collaboration.
• Demonstrated success in conducting research and managing projects in an iterative production environment with ability to manage short- and long-term goals and deliverables.
• Experience in successfully reporting and meeting schedules and milestones of engineering/technology development projects that involve multiple stages and several participants.
• Must complete Cornell University Supervisory Development Training within one year of hire into the position.
• Compliant with all Cornell University and job-related training requirements.

If you have all those things great! We have a few more things that we would prefer you to have but its ok if you dont.

Preferred Qualifications:

• Advanced degree strongly preferred.
• Prior experience working with participatory science remote sensing and climate data.
• Knowledge of birds or ornithology.
• Experience developing DL joint species distribution and abundance models for ecological or conservation applications.
• Demonstrated experience designing AI/ML/DL to support scientific exploration statistical testing and inference.
• Demonstrated experience working in both academic research and industry production environments.

Application Information:

• A Cover Letter and Resume are required for further consideration for this position. When applying through our system please remember to attach your application materials (Cover Letter and Resume) in PDF format.
• Visa Sponsorship of any kind is not available for this position.
• Relocation assistance will not be provided for this position.

What We Offer

Rewards and Benefits

• This position is eligible for a hybrid work arrangement. Employees typically perform this role remotely three (3) days per week and on-campus two (2) days per week. The university reserves the right to modify suspend revoke or terminate the hybrid work arrangement at any time.

• Cornell receives national recognition as an award-winning workplace for our health wellbeing and sustainability.

• Our benefits programs include comprehensive health care options generous retirement contributions access to wellness programs and employee discounts with local and national retail brands. We invite you to follow this link to get more information about our benefits: Understand Your Benefits Working at Cornell.

• Our leave provisions include health and personal leave three weeks of vacation and 13 holidays: Martin Luther King Jr. Day Memorial Day Juneteenth Independence Day Labor Day Thanksgiving and the day after and an end of the year winter break from December 25-January 1. To offer greater flexibility for observing faiths and traditions we also offer two additional floating holidays. Learn more about our generous leave provisions: Holiday and Accrued Time Off Working at Cornell

• Cornells impressive educational benefits include tuition-free Extramural Study and Employee Degree Program tuition aid for external education and Cornell Childrens Tuition Assistance Program. Learn more about our extensive educational benefits: Education Benefits Working at Cornell

• Follow this link to learn more about the Total Rewards of Working at Cornell:

Total Rewards Working at Cornell.

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