F

FICO

Predictive credit risk scoring & analytics

IT Support Specialist

IT Service Desk & End User SupportConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • Experience with Mac and Windows operating systems, System Center Configuration Manager (SCCM), virtual private networks (VPN), RSA, and Active Directory.
  • Awareness of basic networking concepts and technologies, including DHCP, DNS, TCP/IP, and VPN.
  • Knowledge of MSDN accounts, WebEx accounts, and software assignment.
  • Knowledge of the ITIL framework and terminology.
  • Demonstrated problem-solving capabilities.
  • Open to working in a 24x7 environment with rotating shifts and rotating weeks off.

Responsibilities

  • Diagnose, prioritize, troubleshoot, and resolve incidents reported by users via telephone, chat, email, or walk-ins.
  • Identify and escalate tickets requiring urgent attention and action.
  • Log all contacts and document activities and results accurately and completely in the incident management tool.
  • Handle and resolve helpdesk requests involving Outlook, operating systems, printers, standard software, and antivirus.
  • Route or assign tickets to the appropriate support group when necessary.
  • Adhere to established service-level agreements and follow up on tickets in a timely manner.

About the Company

FICO

Predictive credit risk scoring & analytics

FICO provides data analytics and decision-management tools for credit risk and lending, with the FICO score as its flagship measure of consumer credit risk used by lenders. The score is calculated from a user’s credit report data to predict loan repayment likelihood, and FICO software applies analytics and decision rules to guide loan approvals, pricing, fraud detection, and account management. Unlike many competitors, FICO combines a widely adopted score with an end-to-end suite of predictive analytics and decision-management tools that cover the full lending lifecycle. Its goal is to help financial institutions make better lending and risk decisions, prevent fraud, and optimize customer relationships through data-driven, rules-based systems.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Jose, CA
Founded
1956

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