Data Operations Team Lead at Shopic

Tel-Aviv, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

25 Apr, 26

Salary

0.0

Posted On

25 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Operations, Data Quality, Data Workflows, Team Leadership, Algorithm Collaboration, Prioritization, Scripting, Documentation, Communication, Attention to Detail, Annotation Tools, Monitoring Tools, AI, Computer Vision, Process Improvement, Budget Management

Industry

Software Development

Description

Shopic is an AI RetailTech startup specializing in next-generation retail solutions and frictionless shopping experiences. Our technology is powered by advanced computer vision and data analytics. Our products include SmartCart and ShopWatch, a computer vision solution designed to reduce shrink at Self-Checkout stations. We are building data-driven products at scale, and high-quality data is at the core of everything we do. About the Role We are looking for a Data Operations Team Lead to lead and scale our data operations function. This role sits at the intersection of data, algorithms, and operations, and is critical to the success of our computer vision and AI models. You will lead a distributed team responsible for data collection, annotation, quality control, and delivery, while working closely with Algorithm teams to understand model needs, prioritize requests, and ensure reliable, high-quality data pipelines. This is a hands-on leadership role – you will manage people and processes, but also actively design, build, and improve data workflows. Responsabilities Lead and manage the Data Operations team, including annotation teams in Israel and a large remote team in India Serve as the primary interface between Data Operations and Algorithm teams: understand model requirements, prioritize tasks, and plan data delivery Own end-to-end data workflows, from model improvement needs through data definition, annotation guidelines, execution, and delivery Ensure high data quality through close monitoring, validation, troubleshooting, and root-cause analysis Design and maintain clear annotation guidelines, documentation, and training materials Closely manage remote annotation teams, including weekly syncs, hands-on oversight, and deadline management Own and operate the annotation pipeline using industry tools (e.g., CVAT) Monitor progress, track performance, and continuously improve efficiency and quality Own annotation budgets, monthly reporting, and validation of hours and outputs Evaluate, benchmark, and implement new tools and processes in the data and annotation domain Work hands-on with scripts, AI tools, and monitoring systems as needed to support data quality and operations Requirements Proven experience leading teams, preferably including remote or global teams Strong background in data operations, data quality, or data-centric workflows Experience working closely with Algorithm / ML / Computer Vision teams Strong prioritization and execution skills in a fast-paced environment Hands-on technical mindset, including basic scripting and tool usage Ability to create clear documentation, guidelines, and training materials Excellent communication skills and ability to manage multiple stakeholders High ownership mentality and attention to detail Nice to Have Experience managing teams in India Experience with data annotation tools such as CVAT Familiarity with Elastic / Kibana or similar monitoring tools Experience in AI / Computer Vision environments Experience evaluating and implementing new data tools Why Join Shopic? This is a high-impact leadership role with direct influence on the performance of AI models deployed in real-world retail environments. You’ll work with cutting-edge technology, own a critical domain, and help scale data operations at the heart of our products.

Responsibilities

Lead and manage the Data Operations team, ensuring high-quality data pipelines and workflows. Collaborate with Algorithm teams to understand model needs and prioritize data delivery.