Data Specialist Machine Learning Data Operations

Required Qualifications• Excellent communication and interpersonal skills and capacity to ask questions when instructions are not clear enough• Highly organized with strong attention to detail• Strong time management, and able to juggle multiple projects under tight deadlines• Self-motivating with the ability to work independently and with little supervision• Proficiency with macOS, iOS and iPadOS, and with Client apps (Mail, Calendar, Numbers, Keynote)• Consistent quality and speed on repetitive tasks• Ability to independently learn and navigate systems and tools• Able to work on-site in Cupertino 3-5 days per week• Comfort organizing, validating, and spot-checking data files (renaming, reformatting, basic spreadsheet logic)Preferred Qualifications• 3+ years in a professional setting, ideally in data collection, or user study data operations• Experience configuring annotation or customizing data collection tools• Experience with moderating in-person data collection or user studies• Basic knowledge of running cli commands in terminal, and working with python scriptsDescriptionOur Machine Learning Data Ops team builds high-quality datasets at scale to train and evaluate Client AI and ML models. We're looking for a contract Data Specialist to support our Data Program across the full data lifecycle. You'll work hands-on in data collection, annotation, processing, tooling and QA, with flexibility to move between programs as priorities change.

Working Style Fast-paced and changing priorities. You'll work independently with light supervision and collaborate closely with Data Program Managers and QA Leads.Responsibilities• Moderate and setup on-site data collection: Run in-person collections, including recruiting participants, logistics, lab setup, device handling and session support• Annotate pilot projects: Classify, draw bounding boxes, and give subjective ratings on text, image and video assets.• Flag trends and edge cases you see in the data or the tool• QA: Review in-house and vendor-delivered data against guidelines. Score it, give clear feedback, and report issues• Process and packaging datasets: Prepare, organize, rename, convert and validate data assets, and keep deliveries accurate and traceable• Setup and test collection and annotation platforms/devices: Configure projects, tasks and guidelines on platforms/devices.

Test them before launch, and troubleshoot as needed\*\*Only those lawfully authorized to work in the designated country associated with the position will be considered.\*\* \*\*Please note that all Position start dates and duration are estimates and may be reduced or lengthened based upon a client’s business needs and requirements.\*\*