Technical Sourcer - Data Science and Engineering

August 22

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AiDash

WebsiteLinkedInAll Job Openings

Helping core industries be more resilient, efficient and sustainable with satellites & AI

Machine Learning • Big Data • Predictive Analytics • Cognitive • Industrial AI

201 - 500

💰 $10M Convertible Note on 2022-11

Description

• Drive top-of-funnel recruitment efforts by attracting, sourcing, and screening candidates for data science, application engineering, data engineering, and ML platform engineering roles • Collaborate closely with hiring managers and the recruitment team to understand specific talent needs, role requirements, and the broader vision for the R&D organization • Develop and implement data-driven sourcing strategies to attract both active and passive candidates, and nurture and maintain a robust candidate pipeline for current and future hiring needs • Utilize diverse platforms including Google Scholar, LinkedIn Recruiter, GitHub, Stack Overflow, social media, networking events, and industry-specific channels to identify and engage potential candidates • Champion AiDash's employer brand across internal and external platforms, and contribute to employer branding initiatives • Continuously optimize recruitment processes to ensure an outstanding experience for both candidates and interviewers • Provide regular reports on key top-of-funnel metrics, including outreach performance, response rates, and pass-through rates

Requirements

• Minimum of 5 years of experience in technical sourcing, with a proven track record of hiring principal, staff and senior-level data scientists, application engineers, data platform engineers, and ML platform engineers in a startup or high growth environment • Proficiency in using sourcing tools like LinkedIn Recruiter, Google Scholar, GitHub, Boolean, and X-ray searches • Strong understanding of computer vision, AI/ML, and data science technologies • Demonstrated experience in leveraging data and metrics to optimize sourcing strategies, including the ability to track, analyze, and report on key performance indicators such as candidate response rates, pipeline quality, and time-to-fill for technical roles • Excellent communication, relationship-building, and influencing skills, with a collaborative mindset and ability to work independently • Experience in climatetech, remote sensing, geospatial or related fields, including hiring domain experts such as Meteorologists, Climatologists and Arborists, is highly desirable • Passion for technology, and staying current with industry trends and best practices in talent acquisition, particularly within climate tech and AI/ML sectors