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Annotation Analyst

TELUS Digital

  • Ahmedabad, India
  • β‚Ή2.50–3.00 LPA
  • Fresher (0-1 Yrs)
  • Posted Oct 24, 2026
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About the role

TELUS Digital is a global technology services firm that helps enterprises design, build and run digital experiences, data platforms and AI solutions. In India, the company operates several delivery centres that focus on data engineering, machine learning, and customer‑centric digital products. With a strong emphasis on innovation, TELUS Digital invests heavily in up‑skilling its workforce and offers a collaborative environment where fresh talent can work alongside seasoned data scientists and engineers. The Annotation Analyst role is a front‑line position in the AI operations pipeline. As an analyst, you will be responsible for creating high‑quality labelled datasets that power machine‑learning models across various domains such as computer vision, natural language processing, and audio analysis. The position is office‑based in the GIFT City campus of Gandhinagar and follows a 24/7 shift model, meaning you will experience both day and night rotations as part of a dynamic team. Key Responsibilities: 1. Annotate images, text, audio and video data using proprietary labeling tools while strictly adhering to project guidelines. 2. Review and correct existing annotations to ensure consistency and accuracy across the dataset. 3. Validate labelled data against quality metrics and flag any discrepancies for remediation. 4. Collaborate with machine‑learning engineers and data scientists to clarify annotation requirements and provide feedback on guideline improvements. 5. Work on floor‑plan and interior‑layout datasets, applying visual‑spatial reasoning and using tools like AutoCAD or Photoshop where needed. 6. Maintain productivity targets and meet project deadlines without compromising on quality. 7. Document annotation processes, edge cases, and any challenges encountered during the workflow. 8. Participate in regular quality‑control meetings and contribute to continuous‑improvement initiatives. 9. Adapt quickly to updated annotation protocols and new toolsets introduced by the technical team. 10. Support peer training sessions by sharing best practices and tips for efficient labeling. Tech Stack: Specialized annotation platforms, Photoshop, AutoCAD, VFX tools, basic scripting for bulk operations, and standard office productivity suites. Growth Path: Starting as an Annotation Analyst, high performers can progress to Senior Analyst, Team Lead, Quality Assurance Lead, or transition into broader AI Operations roles such as Data Quality Manager or Machine‑Learning Engineer with additional up‑skilling. Why Join TELUS Digital? You will gain hands‑on experience in the fast‑growing AI ecosystem, work on real‑world datasets that impact products used by millions, and enjoy benefits like two‑way cab service, medical and life insurance, and a clear career ladder. The role offers a stable entry‑level salary, exposure to cutting‑edge tools, and the chance to be part of a supportive, innovation‑driven culture.

Eligibility & process

Who can apply

Any graduate or postgraduate who will graduate in 2026 is eligible. No specific engineering or non‑engineering branch is mandated, but candidates must possess at least one of the following certifications: AutoCAD, VFX, Graphic Design, or Photoshop. Freshers are welcomed; prior professional experience is not required. Candidates should have a minimum of 60% aggregate (if mentioned by the recruiter) and must not have any active backlogs at the time of application. Good computer literacy and attention to detail are essential.

Skills & stack

Data annotation Image labeling Attention to detail Photoshop AutoCAD VFX Graphic design Visual‑spatial reasoning Basic computer skills Communication

Selection process

  1. Round 1: Written aptitude test (logical reasoning, quantitative & verbal)
  2. Round 2: Practical annotation test (hands‑on labeling task)
  3. Round 3: HR interview (fitment, shift flexibility, salary discussion)

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Data annotation, Image labeling, Attention to detail, Photoshop, AutoCAD, VFX, Graphic design, Visual‑spatial reasoning, Basic computer skills, Communication) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion TELUS Digital Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join TELUS Digital as a Annotation Analyst?
Highlight TELUS Digital's market reputation, recent tech innovations, and how your skills in Data annotation directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
TELUS Digital β‚Ή2.50–3.00 LPA
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