Project Data Scientist

Los Angeles County Museum Of Natural History Foundation•Los Angeles, CA

About The Position

The Natural History Museums of Los Angeles County (NHMLAC) include the Natural History Museum in Exposition Park and the La Brea Tar Pits in Hancock Park. They operate under the collective vision to inspire wonder, discovery, and responsibility for our natural and cultural worlds. The museums hold one of the world’s most extensive and valuable collections of natural and cultural history—more than 35 million objects—used for groundbreaking scientific and historical research, and community engagement. From NHM’s opening in 1913 as the very first museum in Los Angeles, the organization has entered an exciting new era of transformation with building projects and campaigns, exhibitions, community outreach and impactful audience engagement. NHMLAC’s values—adventurous, inclusive, authentic, and intentional—guide our work and visitor experience, committing us to foster a welcoming, safe and respectful workplace environment where innovation and collaboration thrive and every team member can contribute their unique perspectives to advance our mission. NHMLAC seeks candidates who are aligned with our values and priorities, and are passionate about connecting science with the vibrant and diverse communities we serve throughout Los Angeles. The Natural History Museum of Los Angeles County is seeking a Project Data Scientist for our Research & Collections, Community Science department. The Project Data Scientist will lead data management, analysis, and community-centered data practices across multiple applied, interdisciplinary research projects focused on human-wildlife interactions, biodiversity monitoring, One Health, and environmental justice. Cultivate relationships with community partners and community scientists via supporting data access, data sovereignty, and capacity-building. Produce and disseminate novel research findings via peer-reviewed publications and both academic- and public-facing outreach.

Requirements

Ph.D. in a relevant field OR a Master’s degree with strong, proven data science experience. Examples of relevant fields are environmental science, environmental justice, ecology, conservation science, environmental education, biology, environmental policy, etc.
Record of publishing peer-reviewed papers.
Expertise in data management and analysis, including conducting GIS analyses and/or conducting other ecological analyses.
Proficiency in R, Python, and/or similar tools.
At least 2 years of experience working with community members, including mentoring students.
Must have led at least one research project from start to finish (i.e., resulting in a peer-reviewed publication or completed thesis) in a relevant field.
A demonstrated excellence in oral and written communication.
Passionate about communicating science to a diversity of public audiences.
Excellent collaboration and project management skills, including working with networks of diverse collaborators and participants.

Nice To Haves

Experience with community-engaged research is preferred.
Bilingual in Spanish and English highly preferred but not required.

Responsibilities

Develop and maintain data systems, workflows, and documentation across projects in the Community Science office (~30% of time).
Clean, integrate, and analyze datasets regarding ecology, human-wildlife interactions, community science, and environmental justice (~25% of time).
Lead and contribute to peer-reviewed publications and research outputs (~15% of time).
Collaborate with community partners on data governance, access, and sovereignty, including creating dashboards, summaries, and highlights for community partners (~10% of time).
Support the creation, revision, streamlining, and improvement of research projects led by the Community Science team (~10% of time).
Create data visualizations for scientific and community audiences (~5% of time).
Develop and write novel grant and external funding proposals, under the supervision of the Assistant Curator of Community Science (~5% of time).
Support training, mentorship, and capacity-building within team and community, including mentoring and potentially collaborating with graduate students and post-baccalaureate students on research projects related to human-wildlife interactions, community science, participatory science, and biodiversity monitoring (~5% of time).