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MoneyTap logo — MoneyTap ServiceNow Intern in Bengaluru, Karnataka
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ServiceNow Intern

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Location

Bengaluru, Karnataka

Work Mode

Hybrid

Duration

2 months

Stipend

₹29,000/mo

Start Date

Immediate / Rolling

Openings

3 positions

Type

Full-time

Category

Data Science

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About the Internship

Join MoneyTap in Bengaluru as a ServiceNow Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on ServiceNow platform work work. About the role As a ServiceNow Intern at MoneyTap, your core focus will be…

About MoneyTap

MoneyTap offers a mentor-led ServiceNow Intern in Bengaluru with live project work in data science, a stipend of ₹29,000/month and a Pre-Placement Offer opportunity for strong performers.
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Bengaluru, KarnatakaVerified employer3 openings
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Skills Required

ServiceNowITSM ProcessesFlow DesignerJavaScriptBusiness RulesService CatalogIntegrations & RESTUpdate SetsReportingDocumentation

Who Can Apply

  • Final-year students and recent graduates from B.E./B.Tech (any branch), BCA/MCA, B.Sc (Computer Science / IT) or MCA who are based in or willing to work from Bengaluru. You should be keen to learn ServiceNow, ITSM Processes, Flow Designer on real projects and able to write clearly. Freshers are welcome — no prior work experience is required, and a strong project portfolio matters more than a long CV.

Perks

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursDirect access to the team that owns the data you work on

Interview & Selection Process

4 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects
  3. 3Practical assignment or case study with a short walkthrough
  4. 4HR discussion — stipend, start date, expectations and offer
29,000/month

Stipend · 2 months

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Openings3 positions
Applicants0 applied
ModeHybrid
CategoryData Science
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