Data Collection Specialist

Canopy is a company with a unique mission, solving for the large and growing problem of theft from vehicles. With our patented cutting edge AI technologies, we are determined to provide peace of mind to the millions with items in their vehicles that are vulnerable to theft.We are looking for a Data Collection Specialist to scale up and continuously improve our data collection and annotation efforts, with a direct impact on the quality of our AI/Machine Learning-based solution. If you have an appetite for autonomy, task diversity, structuring data, assuring data quality, growing as a people and project manager and making a tangible impact, please consider joining us!Responsibilities:
Management of Data Collection: manage the gathering of real-world vehicle intrusion data — images, videos, audio, and other sensor data using our proprietary hardware. Analyze data from the field, identify and address anomalies, design and apply data collection improvements. Management of Data Annotation Projects: gather machine learning project requirements from multiple stakeholders and work with machine learning engineers to transform these requirements into clearly documented annotation rules and objectives. Make adjustments as project requirements change, and maintain clear written documentation. Continuous improvement: continuously refine our data collection and annotation guidelines. Identify labeling inefficiencies and design related improvements. Identify labeling edge cases and emit recommendations about their processing. Management of Resources: collaborate with our annotation suppliers to ensure annotations are of high-integrity and adhere to our annotation guidelines. Review the annotated data and manage corrections as needed; ensure the quality of the data labels. Manage the capability to hire local temporary workers for specific annotation projects, and supervise the temporary workers during the project.Coach new data annotators with annotation guidelines and provide feedback to improve training documentation Field Testing: apply our solutions in real-world scenarios, contribute to innovative advancements. Develop a first-hand feel for the practical factors of vehicle security sensing, and be one of our “persons on the ground” to ensure that future generations of the company’s intrusion sensing AI keep delivering in real life condition. You will have the opportunity to experiment with top-line Ford vehicles, including pick up trucks.
Extremely high attention to detail with an appreciation for data integrity. Excellent communicator, ability to create and maintain detailed documentation.
Computer skills: Comfortable navigating and working within a linux environment, moving data between devices, shell scripting, common linux commands, simple text editors like vi, etc. Python programming at an autonomous level, or substantiated interest in learning Python programming.
Evidence of prior experience in working with data or substantiated interest in data management, where data includes both unstructured binary data such as images, videos, audio files, etc., and structured data such as text databases, tagging systems, etc. Evidence of leadership experience; leadership skills and interest substantiated by either professional or social activities. Must hold a valid UK driving license.
Willingness and ability to travel domestically and internationally. Additional Requirements (specific to this role)
Office or other indoor work that includes sitting, standing, typing, communicating and observing with light physical demands such as occasionally lifting or moving materials less than 20 pounds Work is generally performed in a well-lit, temperature-controlled indoor environment with occasional exposure to the outdoors or any number of elements. Work is performed with exposure to any number of elements which may occasionally require some precautions such as safety glasses, protective clothing, ear protection, etc. Ability to travel in-state and out-of-state or globally. Ability to work irregular shifts and extended hours, including evenings and weekends. Preferred Qualifications: Preferred qualifications are additional measurable and job‐related levels of experience, knowledge, and or/skill the ideal employee would have.
Prior machine learning experience including familiarity with the main underlying concepts, or substantiated interest in machine learning. Experience working with teams developing products that have computer vision and machine learning at the heart of their application (object detection, semantic segmentation, keypoint estimation, scene understanding, etc.) Work EligibilityMust be a UK Citizen and eligibility to work in London Health Care Plan (Medical, Dental & Vision) Retirement Plan (401k, IRA) Life Insurance (Basic, Voluntary & AD&D) Paid Time Off (Vacation, Sick & Public Holidays) Family Leave (Maternity, Paternity) Short Term & Long Term Disability Training & Development Compensation Range Exact compensation may vary based on skills, experience, and location. Base Salary: £43,411.20 - £65,973.60 GBPAnnual Bonus: 10%Diversity, Equity and Inclusion: At Canopy, we're on a mission to end theft from vehicles and revolutionize vehicle security by building cutting-edge technology. We will achieve this by prioritizing individuals and staying attuned to the evolving needs of our people, users, and industry trends. We foster a workplace culture that embraces diversity and authenticity, enabling us to flourish as a team of exceptional individuals working towards a common purpose. We gain a deeper understanding of our users' experiences by continuously improving our skills and expanding our knowledge. A more diverse, equitable, and inclusive Canopy leads to greater innovation and success.Equal Opportunity:
Canopy does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.
#J-18808-Ljbffr