Data Annotation & Data Labelling (Work From Home)

Zensar’s interview process typically starts with an online aptitude test that evaluates logical reasoning, quantitative ability, and basic data‑handling skills. Successful candidates move to a technical interview where they discuss annotation tools, data quality concepts, and may solve a short case study. The final HR round assesses cultural fit, communication skills, and readiness for remote work. Overall difficulty is moderate, and thorough preparation of data‑annotation basics and aptitude practice greatly improves chances.

Zensar promotes a collaborative, learning‑centric environment where employees are encouraged to upskill through internal academies and certifications. The company offers flexible work arrangements, a balanced work‑life culture, and clear career progression paths, making it an attractive place for fresh talent to grow.

Any graduate (B.Tech, B.Sc, B.Com, BA) with a minimum of 60% aggregate in the final year. Open to all streams; engineering or science backgrounds preferred. No active backlogs at the time of joining. Must possess a personal laptop and stable internet connection. Candidates should be able to commit to the full two‑month assignment starting 1st September 2026.

Round 1: Online aptitude & data‑handling test → Round 2: Technical interview focusing on annotation tools, data quality concepts, and problem‑solving → Round 3: HR interview covering motivation, remote‑work suitability, and cultural fit

Zensar Technologies is a global digital solutions and technology services firm that partners with enterprises across banking, healthcare, manufacturing, retail, and many other sectors. A subsidiary of the RPG Group, Zensar has its headquarters in Pune, India, and operates delivery centers in the United States, United Kingdom, Mexico, South Africa, and several other countries. The company focuses on digital transformation, cloud migration, data analytics, and intelligent automation, helping clients modernize legacy systems and adopt emerging technologies. Zensar’s culture is built around continuous learning, collaborative problem‑solving, and a strong emphasis on employee growth, which has earned it consistent recognition on employer ranking platforms. The role of Data Annotation & Data Labelling is a short‑term, work‑from‑home opportunity designed for candidates who can contribute to Zensar’s data‑driven projects. Over a two‑month assignment starting 1st September 2026, you will be responsible for preparing high‑quality training data that powers machine‑learning models used in computer‑vision, natural‑language‑processing, and other AI initiatives. The position offers a stipend of INR 50,000 per month and requires you to have a personal laptop to run annotation tools securely from your home. Key Responsibilities: 1. Review raw datasets (images, video, text) and apply precise labeling according to project guidelines. 2. Use annotation platforms such as Labelbox, Scale AI, or in‑house tools to mark objects, boundaries, and attributes. 3. Ensure consistency and accuracy by following detailed annotation standards and performing quality checks. 4. Collaborate with the data‑science team to clarify ambiguous cases and improve labeling instructions. 5. Maintain documentation of labeling decisions and update guidelines as needed. 6. Track progress against daily and weekly targets, reporting any blockers promptly. 7. Perform basic data preprocessing tasks like resizing images or normalizing text. 8. Participate in regular virtual sync‑ups and provide feedback for process improvement. 9. Adhere to data‑privacy and security policies while handling sensitive information. 10. Deliver annotated datasets within the stipulated timelines, ready for model training. Tech Stack & Tools: Annotation platforms (Labelbox, Scale AI), image/video editing tools (Photoshop, VLC), basic scripting in Python for automation, Excel/Google Sheets for tracking, and version‑control basics (Git) for dataset versioning. Growth Path: Although the assignment is short‑term, high‑performing contributors may be considered for longer contracts or full‑time roles in Zensar’s AI and analytics divisions. The exposure to real‑world AI pipelines can serve as a springboard for careers in data science, machine‑learning engineering, or quality assurance. Why Join Zensar? You will work with a globally recognized technology leader, gain hands‑on experience with AI data pipelines, and enjoy the flexibility of a remote setup. The role offers a competitive stipend, a clear learning curve, and the possibility of future opportunities within a company known for nurturing talent and promoting internal mobility.