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Saviynt Developer

PwC

  • Bengaluru, India
  • Competitive Package (Best in Industry)
  • 3-8 Yrs
  • Posted Yesterday
HR
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About the role

  • Minimum 4+ years of experience in implementing and managing IAM solutions Minimum 3+ years of hands-on experience implementing and supporting Saviynt Enterprise Identity Cloud (EIC) platforrn in enterprise environments Saviynt Certified Professional (SCP) or Saviynt Certified Advanced Professional (SCAP) certification is highly desirable Preferred candidate profile

Eligibility & process

Who can apply

Experience: 3-8 Yrs. Open to matching qualifications.

Skills & stack

Implementation And Integration Projects Saviynt Integration Sailpoint Project Data Structures & Algorithms Python/Java System Design

Selection process

  1. Online Assessment / Technical Interview Rounds / HR Review

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 (Implementation And Integration Projects, Saviynt, Integration, Sailpoint, Project, Data Structures & Algorithms, Python/Java, System Design) & 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 PwC 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 PwC as a Saviynt Developer?
Highlight PwC's market reputation, recent tech innovations, and how your skills in Implementation And Integration Projects 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.
PwC Competitive Package (Best in Industry)
Recruiter Resume Apply
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